Nakamoto proof-of-work ledger consensus currently underlies the majority of deployed cryptocurrencies and smart-contract blockchains. While a long and fruitful line of work studying the provable security guarantees of this mechanism has succeeded to identify its exact security region---that is, the set of parametrizations under which it possesses asymptotic security---the existing theory does not provide concrete settlement time guarantees that are tight enough to inform practice. In this work we provide a new approach for obtaining concrete and practical settlement time guarantees suitable for reasoning about deployed systems. We give an efficient method for computing explicit upper bounds on settlement time as a function of primary system parameters: honest and adversarial computational power and a bound on network delays. We implement this computational method and provide a comprehensive sample of concrete bounds for several settings of interest. We also analyze a well-known attack strategy to provide lower bounds on the settlement times. For Bitcoin, for example, our upper and lower bounds are within 90 seconds of each other for 1-hour settlement assuming 10 second network delays and a 10% adversary. In comparison, the best prior result has a gap of 2 hours in the upper and lower bounds with the same parameters.

Nath and Sarkar propose algorithms to improve the efficiency of Diffie-Hellman key agreement using Curve448. In this note an error in the proof of correctness of the subtraction algorithm is described. An alternative argument is offered to fix this error without changing the algorithm or statement of correctness.

Li and Micciancio (Eurocrypt 2021) shattered a widespread misconception regarding the security of protocols based on cpa-secure homomorphic encryption (HE). They showed an attack breaking security of HE-based protocols provided that the protocol employs an HE scheme for approximate numbers, like CKKS, and the adversary sees decrypted ciphertexts. However, their attack fails when employing exact HE schemes, like BGV, or denying access to decrypted data. We show that the Li-Micciancio attack is only the tip of the iceberg: 1)We exhibit an input-recovery attack completely breaking the privacy of a wide and natural family of HE-based protocols, including protocols using only exact HE-schemes and with an adversary exposed solely to encrypted data. This proves that cpa-security is insufficient to ensure privacy in a much broader context than previously known. 2)To address the threat exhibited by our attack we introduce sufficient conditions, on either the encryption scheme or the protocol, that do guarantee privacy: (a) Every HE scheme with a sanitization algorithm (e.g., BGV and FHEW) can be transformed into a ``sanitized" scheme so that protocols instantiated with it preserve privacy against malicious adversaries. (b) Moreover, we characterize a natural sub-family of these protocols for which cpa-security does suffice to guarantee privacy, albeit against semi-honest adversaries. To prove (2a) we define a notion of circuit-privacy+ that lies between semi-honest and malicious circuit-privacy and realize it from existing schemes; this may be of independent interest.

Secret-sharing is one of the most basic and oldest primitives in cryptography, introduced by Shamir and Blakely in the 70s. It allows to strike a meaningful balance between availability and confidentiality of secret information. It has a host of applications most notably in threshold cryptography and multi-party computation. All known constructions of secret sharing (with the exception of those with a pathological choice of parameters) require access to uniform randomness. In practice, it is extremely challenging to generate a source of uniform randomness. This has led to a large body of research devoted to designing randomized algorithms and cryptographic primitives from imperfect sources of randomness. Motivated by this, 15 years ago, Bosley and Dodis asked whether it is even possible to build 2-out-of-2 secret sharing without access to uniform randomness. In this work, we make progress towards resolving this question. We answer this question for secret sharing schemes with important additional properties, i.e., either leakage-resilience or non-malleability. We prove that, unfortunately, for not too small secrets, it is impossible to construct any of 2-out-of-2 leakage-resilient secret sharing or 2-out-of-2 non-malleable secret sharing without access to uniform randomness. Given that the problem whether 2-out-of-2 secret sharing requires uniform randomness has been open for a long time, it is reasonable to consider intermediate problems towards resolving the open question. In a spirit similar to NP-completeness, we study how the existence of a t-out-of-n secret sharing without access to uniform randomness is related to the existence of a t'-out-of-n' secret sharing without access to uniform randomness for a different choice of the parameters t,n,t',n'.

We formally introduce, define, and construct memory-hard puzzles. Intuitively, for a difficulty parameter $t$, a cryptographic puzzle is memory-hard if any parallel random access machine (PRAM) algorithm with "small" cumulative memory complexity ($\ll t^2$) cannot solve the puzzle; moreover, such puzzles should be both "easy" to generate and be solvable by a sequential RAM algorithm running in time $t$. Our definitions and constructions of memory-hard puzzles are in the standard model, assuming the existence of indistinguishability obfuscation ($i\mathcal{O}$) and one-way functions (OWFs), and additionally assuming the existence of a memory-hard language. Intuitively, a language is memory-hard if it is undecidable by any PRAM algorithm with "small" cumulative memory complexity, while a sequential RAM algorithm running in time $t$ can decide the language. Our definitions and constructions of memory-hard objects are the first such definitions and constructions in the standard model without relying on idealized assumptions (such as random oracles). We give two applications which highlight the utility of memory-hard puzzles. For our first application, we give a construction of a (one-time) memory-hard function (MHF) in the standard model, using memory-hard puzzles and additionally assuming $i\mathcal{O}$ and OWFs. For our second application, we show any cryptographic puzzle (e.g., memory-hard, time-lock) can be used to construct resource-bounded locally decodable codes (LDCs) in the standard model, answering an open question of Blocki, Kulkarni, and Zhou (ITC 2020). Resource-bounded LDCs achieve better rate and locality than their classical counterparts under the assumption that the adversarial channel is resource bounded (e.g., a low-depth circuit). Prior constructions of MHFs and resource-bounded LDCs required idealized primitives like random oracles.

Timed-release encryption can encrypt a message to a future time such that it can only be decrypted after that time. Potential applications include sealed bid auctions, scheduled confidential transactions, and digital time capsules. To enable such applications as decentralized smart contracts, we explore how to use timed-release encryption on blockchains. Practical constructions in literature rely on a trusted server (or servers in a threshold setting), which periodically publishes an epoch-specific decryption key based on a long-term secret. Their main idea is to model time periods or epochs as identities in an identity-based encryption scheme. However, these schemes suffer from a fatal flaw: an epoch’s key does not let us decrypt ciphertexts locked to prior epochs. Paterson and Quaglia [SCN'10] address this concern by having encryption specify a range of epochs when decryption is allowed. However, we are left with an efficiency concern: in each epoch, the server(s) must publish (via a smart contract transaction) a decryption key of size logarithmic in the lifetime (total number of epochs). For instance, on Ethereum, for a modest lifetime spanning 2 years of 1-minute long epochs, a server must spend over \$6 in gas fees, every minute; this cost multiplies with the number of servers in a threshold setting. We propose a novel timed-release encryption scheme, where a decryption key, while logarithmic in size, allows incremental updates, wherein a short update key (single group element) is sufficient to compute the successive decryption key; our decryption key lets the client decrypt ciphertexts locked to any prior epoch. This leads to significant reduction is gas fees, for instance, only \$0.30 in the above setting. Moreover, ciphertexts are also compact (logarithmic in the total lifetime), and encryption and decryption are on the order of few milliseconds. Furthermore, we decentralize the trust among a number of servers, so as to tolerate up to a threshold number of (malicious) corruptions. Our construction is based on bilinear pairing, and adapts ideas from Canetti et al.'s binary tree encryption [Eurocypt 2003] and Naor et al.'s distributed pseudorandom functions [Eurocrypt 1999].

Since its invention in 1982, the LLL lattice reduction algorithm (Lenstra, Lenstra, Lovasz 1982) has found countless applications. In cryptanalysis, the two most prominent applications of LLL and its generalisations --e.g. Slide, BKZ and SD-BKZ-- are factoring RSA keys with extra information on the secret key via Coppersmith's method and the cryptanalysis of lattice-based schemes. After almost 40 years of cryptanalytic applications, predicting and optimising lattice reduction algorithms remains an active area of research. While we do have theorems bounding the worst-case performance of these algorithms, those bounds are asymptotic and not necessarily tight when applied to practical or even cryptographic instances. Reasoning about the behaviour of those algorithms relies on heuristics and approximations, some of which are known to fail for relevant corner cases. Decades after Lenstra, Lenstra, and Lovász gave birth to this fascinating and lively research area, this state of affairs became a more pressing issue recently. Motivated by post-quantum security, standardisation bodies, governments and industry started to move towards deploying lattice-based cryptographic algorithms. This spurred the refinement of those heuristics and approximations, leading to a better understanding of the behaviour of these algorithms over the last few years. Lattice reduction algorithms, such as LLL and BKZ, proceed with repeated local improvements to the lattice basis, and each such local improvement means solving the short(est) vector problem in a lattice of a smaller dimension. Therefore, two questions arise: how costly is it to find those local improvements and what is the global behaviour as those improvements are applied. While those two questions may not be perfectly independent, we will, in this survey, focus on the second one, namely, the global behaviour of such algorithms, given oracle access for finding local improvements. Our focus on the global behaviour is motivated by our intent to draw more of the community's attention to this aspect. We will take a particular interest in the behaviour of such algorithms on a specific class of lattices, underlying the most popular lattice problems to build cryptographic primitives, namely the LWE problem and the NTRU problem. We will emphasise on the approximations that have been made, their progressive refinements and highlight open problems to be addressed.

We present probabilistic dynamic I/O automata, a framework to model dynamic probabilistic systems. Our work extends dynamic I/O Automata formalism of Attie & Lynch to probabilistic setting. The original dynamic I/O Automata formalism included operators for parallel composition, action hiding, action renaming, automaton creation, and behavioral sub-typing by means of trace inclusion. They can model mobility by using signature modification. They are also hierarchical: a dynamically changing system of interacting automata is itself modeled as a single automaton. Our work extends to probabilistic settings all these features. Furthermore, we prove necessary and sufficient conditions to obtain the implementation monotonicity with respect to automata creation and destruction. Our construction uses a novel proof technique based on homomorphism that can be of independent interest. Our work lays down the foundations for extending composable secure-emulation of Canetti et al. to dynamic settings, an important tool towards the formal verification of protocols combining probabilistic distributed systems and cryptography in dynamic settings (e.g. blockchains, secure distributed computation, cybersecure distributed protocols etc).

Multi-party computation (MPC) allows two or more parties to jointly and securely compute functions over private inputs. Cryptographic protocols that realize MPC require functions to be expressed as Boolean or arithmetic circuits. Deriving such circuits is either done manually, or with hardware synthesis tools and specialized MPC compilers. Unfortunately, such existing tools compile only from a single front-end language and neglect decades of research for optimizing regular compilers. In this paper, we make MPC practical for developers by automating circuit compilation based on the compiler toolchain LLVM. For this, we develop an LLVM optimizer suite consisting of multiple transform passes that operate on the LLVM intermediate representation (IR) and gradually lower functions to circuit level. Our approach supports various front-end languages (currently C, C++, and Fortran) and takes advantage of powerful source code optimizations built into LLVM. We furthermore make sure to produce circuits that are optimized for MPC, and even offer fully automated post-processing for efficient post-quantum MPC. We empirically measure the quality of our compilation results and compare them to the state-of-the-art specialized MPC compiler HyCC (Büscher et al., CCS'2018). For all benchmarked HyCC example applications (e.g., biomatch and linear equation solving), our highly generalizable approach achieves similar quality in terms of gate count and composition.

Consensus protocols enable $n$ parties, each holding some input string, to agree on a common output even in the presence of corrupted parties. While the problem is well understood in the classic byzantine setting, recent work has pushed to understand the problem when realistic types of failures are considered and a majority of parties may be corrupt. Garay and Perry consider a model with both byzantine and crash faults and develop a corruption-optimal protocol with perfect security tolerating $t_c$ crash faults and $t_b$ byzantine faults for $n>t_c+3t_b$. Follow up work by Zikas, Hauser, and Maurer extends the model by considering receive-corrupt parties that may not receive messages sent to them, and send-corrupt parties whose sent messages may be dropped. Otherwise, receive-corrupt and send-corrupt parties behave honestly and their inputs and outputs are considered by the security definitions. Zikas, Hauser, and Maurer gave a perfectly secure, linear-round protocol for $n > t_r+t_s+3t_b$, where $t_r$ and $t_s$ represent thresholds on the number of parties that are receive- or send-corrupted. In this paper we ask ``what are optimal thresholds in the cryptographic setting that can be tolerated with such mixes of corruptions and faults?" We develop an expected-constant round protocol tolerating $n > t_r+2t_s+2t_b$. We are unable to prove optimality of our protocol's corruption budget in the general case; however, when we constrain the adversary to either drop all or none of a sender's messages in a round, we prove our protocol achieves an optimal threshold of $n > t_r+t_s+2t_b$. We denote this weakening of a send corruption a \emph{spotty send corruption}. In light of this difference in corruption tolerance due to our weakening of a send corruption, we ask ``how close (with respect to corruption thresholds) to a byzantine corruption is a send corruption?" We provide a treatment of the difficulty of dealing with send corruptions in protocols with sublinear rounds. As an illustrative and surprising example (even though not in sublinear rounds), we show that the classical Dolev-Strong broadcast protocol degrades from $n > t_b$ corruptions in the byzantine-only model to $n > 2t_s+2t_b$ when send-corrupt parties' outputs must be consistent with honest parties; we also show why other recent dishonest-majority broadcast protocols degrade similarly. We leave open the question of optimal corruption tolerance for both send- and byzantine corruptions.

Secure comparison (SC) is an essential primitive in Secure Multiparty Computation (SMC) and a fundamental building block in Privacy-Preserving Data Analytics. Although secure comparison has been studied since the introduction of SMC in the early 80s and many protocols have been proposed, there is still room for improvement, especially providing security against malicious adversaries who form the majority among the participating parties. It is not hard to develop an SC protocol secure against malicious majority based on the current state of the art SPDZ framework. SPDZ is design to work for arbitrary polynomially-bounded functionalities, and it may not provide the most efficient SMC implementation for a specific task, such as SC. In this paper, we propose a novel compiler that is specifically designed to convert most existing SC protocols with semi-honest security into the ones secure against the malicious majority. This compiler provides a flexible and efficient way to achieve both covert and active security for passively secure SC protocols.

Micro-architectural leakage is a reality even on low- to midrange commercial processors. Dealing with it is expensive, because micro-architectural leakage is often only discovered after implementation choices have been made (i.e. when evaluating the concrete implementation). We demonstrate that it is feasible, using a recent leakage modelling technique, to reverse engineer significant elements of the micro-architectural leakage of a mid-range commercial processor in a “grey-box” setting. Our approach first recovers the micro-architectural features of each stage in the pipeline, and the leakage of elements that are known to produce glitches. To put our reverse engineered micro-architectural leakage in context, we compare and contrast a leakage analysis of a relevant piece of masking code. More specifically, we compare the leakage that we would anticipate given our analysis, and predictions of the to-date most sophisticated leakage simulators (e.g. ELMO and MAPS) on the same piece of code. Our research demonstrates that reverse engineering of micro-architectural components (and their leakage) is clearly feasible using available side channel leakage, and following, it should be possible to build more accurate leakage simulators.

Property-preserving hash functions allow for compressing long inputs $x_0$ and $x_1$ into short hashes $h(x_0)$ and $h(x_1)$ in a manner that allows for computing a predicate $P(x_0, x_1)$ given only the two hash values without having access to the original data. Such hash functions are said to be adversarially robust if an adversary that gets to pick $x_0$ and $x_1$ after the hash function has been sampled, cannot find inputs for which the predicate evaluated on the hash values outputs the incorrect result. In this work we construct robust property-preserving hash functions for the hamming-distance predicate which distinguishes inputs with a hamming distance at least some threshold $t$ from those with distance less than $t$. The security of the construction is based on standard lattice hardness assumptions. Our construction has several advantages over the best known previous construction by Fleischhacker and Simkin (Eurocrypt 2021). Our construction relies on a single well-studied hardness assumption from lattice cryptography whereas the previous work relied on a newly introduced family of computational hardness assumptions. In terms of computational effort, our construction only requires a small number of modular additions per input bit, whereas the work of Fleischhacker and Simkin required several exponentiations per bit as well as the interpolation and evaluation of high-degree polynomials over large fields. An additional benefit of our construction is that the description of the hash function can be compressed to $\lambda$ bits assuming a random oracle. Previous work has descriptions of length $\mathcal{O}(\ell \lambda)$ bits for input bit-length $\ell$. We prove a lower bound on the output size of any property-preserving hash function for the hamming distance predicate. The bound shows that the size of our hash value is not far from optimal.

We introduce a technique to obtain practical speed up for relation collection in class group computations. The idea is to perform a pseudo-random walk over the ideals. The ideals visited by the walk are used in the manner exactly as in the previous algorithm due to Gélin (2018). Under the heuristic assumption that the ideals visited by the walk behave as the ideals randomly generated in Gélin’s algorithm, the asymptotic complexity of the new algorithm remains the same as that of Gélin’s algorithm. The main advantage of the new method over Gélin’s method is that the pseudo-random walk requires a single ideal multiplication to generate the next ideal in the walk, whereas Gélin’s algorithm requires a number of ideal multiplications to generate each ideal to be tested. We have made Magma implementations of both the new algorithm and Gélin’s algorithm. Timing results confirm that there is indeed a substantial practical speed-up in relation collection by the new algorithm over Gélin’s algorithm.

CAS-Lock (proposed in CHES2020), is an advanced logic locking technique that harnesses the concept of single-point function in providing SAT-attack resiliency. It is claimed to be powerful and efficient enough in mitigating state-of-the-art attacks against logic locking techniques. Despite the security robustness of CAS-Lock as claimed by the authors, we expose a serious vulnerability by exploiting the same and device a novel attack algorithm. The proposed attack can reveal the correct key by extracting the Distinguishing Input Patterns (DIPs) pertaining to a carefully chosen key simulation of the locked design. The correct key is obtained from the combination of elements from the set of extracted DIPs. Our attack is successful against various AND/OR cascaded-chain configurations of CAS-Lock and reports a 100% success rate in recovering the correct key.

We take a look at the current implementation of NTRU submitted to the NIST post-quantum standardization project, and identify two strong sources of leakage in the unpacking of the secret key. The strength of the leakages is due to the target processor handling data with very different Hamming weight depending on parts of the secret key. We focus on using only these strong leakages, present a single-trace side-channel attack that reliably recovers a large portion of the secret key, and use lattice reduction techniques to find the remaining parts. Further, we show how small changes to the implementation greatly reduces the leakage without any overhead.

The amount of encrypted Internet traffic almost doubles every year thanks to the wide adoption of end-to-end traffic encryption solutions such as IPSec, TLS and SSH. Despite all the benefits of user privacy the end-to-end encryption provides, the encrypted internet traffic blinds intrusion detection system (IDS) and makes detecting malicious traffic hugely difficult. The resulting conflict between the user's privacy and security has demanded solutions for deep packet inspection (DPI) over encrypted traffic. The approach of those solutions proposed to date is still restricted in that they require intensive computations during connection setup or detection. For example, BlindBox, introduced by Sherry et al. (SIGCOMM 2015) enables inspection over the TLS-encrypted traffic without compromising users' privacy, but its usage is limited due to a significant delay on establishing an inspected channel. PrivDPI, proposed more recently by Ning et al. (ACM CCS 2019), improves the overall efficiency of BlindBox and makes the inspection scenario more viable.Despite the improvement, we show in this paper that the user privacy of Ning et al.'s PrivDPI can be compromised entirely by the rule generator without involving any other parties, including the middlebox. Having observed the difficulties of realizing efficiency and security in the previous work, we propose a new DPI system for encrypted traffic, named ``Practical and Privacy-Preserving Deep Packet Inspection (P2DPI)''. P2DPI enjoys the same level of security and privacy that BlindBox provides. At the same time, P2DPI offers fast setup and encryption and outperforms PrivDPI. Our results are supported by formal security analysis. We implemented our P2DPI and comparable PrivDPI and performed extensive experimentation for performance analysis and comparison.

The main conceptual contribution of this paper is a unification of two leading paradigms for constructing succinct argument systems, namely Kilian's protocol and the BMW (Biehl-Meyer-Wetzel) heuristic. We define the notion of a multi-extractable somewhere statistically binding (meSSB) hash family, an extension of the notion of somewhere statistically binding hash functions (Hubacek and Wichs, ITCS 2015), and construct it from LWE. We show that when instantiating Kilian's protocol with a meSSB hash family, the first two messages are simply an instantiation of the BMW heuristic. Therefore, if we also instantiate it with a PCP for which the BMW heuristic is sound, e.g., a computational non-signaling PCP, then the first two messages of the Kilian protocol is a sound instantiation of the BMW heuristic. This leads us to two technical results. First, we show how to efficiently convert any succinct non-interactive argument (SNARG) for BatchNP into a SNARG for any language that has a computational non-signaling PCP. Put together with the recent and independent result of Choudhuri, Jain and Jin (Eprint 2021/808) which constructs a SNARG for BatchNP from LWE, we get a SNARG for any language that has a computational non-signaling PCP, including any language in P, but also any language in NTISP (non-deterministic bounded space), from LWE. Second, we introduce the notion of a somewhere statistically sound (SSS) interactive argument, which is a hybrid between a statistically sound proof and a computationally sound proof (a.k.a. an argument), and * prove that Kilian's protocol, instantiated as above, is an SSS argument; * show that the soundness of SSS arguments can be proved in a straight-line manner, implying that they are also post-quantum sound if the underlying assumption is post-quantum secure; and * conjecture that constant-round SSS arguments can be soundly converted into non-interactive arguments via the Fiat-Shamir transformation.

This paper studies the challenges of creating a mobile device based voting client. We discuss the issues related to standalone and mobile browser based voting applications. In both cases we discuss the problems of vote privacy, integrity and voting channel availability. We conclude that neither of the options can currently achieve the level of security PC-based voting clients can provide, with the attack surface being larger in the case of mobile browser based voting application.

Volumetric leakage in encrypted databases had been overlooked by the community for a long time until Kellaris et al. (CCS ’16) proposed the first database reconstruction attack leveraging communication volume. Their attack was soon improved and several query recovery attacks were discovered recently. In response to the advancements of volumetric leakage attacks, volume-hiding searchable symmetric encryption (SSE) schemes have been proposed (Kamara and Moataz, Eurocrypt ’19 & Patel et al., CCS ’19). In these schemes, the database is padded in a clever way so that the volume (i.e., the number of responses) for any search query is the same or computationally indistinguishable while keeping the storage complexity and search complexity as small as possible. Unfortunately, existing volume-hiding SSE schemes do not support atomic updates (i.e., addition/deletion of an arbitrary keyword-document pair), which is the most common update operation considered in the SSE literature. Meanwhile, recent volumetric attacks (Wang et al., EuroS&P ’20 & Blackstone et al., NDSS ’20) indeed target dynamic databases. We initiate a formal study of volume-hiding dynamic SSE. We extend the existing definition of volume-hiding leakage function into the dynamic setting and present efficient constructions VH-DSSE and VH-DSSE^k . VH-DSSE suffers from non-negligible correctness error. To remedy the disadvantage of VH-DSSE, we propose a multi-copy construction VH-DSSE^k that amplifies correctness by parallel repetition. As a side contribution, both VH-DSSE and VH-DSSE^k satisfy the strongest notions of backward-privacy, which is the first one in the literature, to the best of our knowledge.

In two of the main areas of post-quantum cryptography, based on lattices and codes, nearest neighbor techniques have been used to speed up state-of-the-art cryptanalytic algorithms, and to obtain the lowest asymptotic cost estimates to date [May-Ozerov, Eurocrypt'15; Becker-Ducas-Gama-Laarhoven, SODA'16]. These upper bounds are useful for assessing the security of cryptosystems against known attacks, but to guarantee long-term security one would like to have closely matching lower bounds, showing that improvements on the algorithmic side will not drastically reduce the security in the future. As existing lower bounds from the nearest neighbor literature do not apply to the nearest neighbor problems appearing in this context, one might wonder whether further speedups to these cryptanalytic algorithms can still be found by only improving the nearest neighbor subroutines. We derive new lower bounds on the costs of solving the nearest neighbor search problems appearing in these cryptanalytic settings. For the Euclidean metric we show that for random data sets on the sphere, the locality-sensitive filtering approach of [Becker-Ducas-Gama-Laarhoven, SODA 2016] using spherical caps is optimal, and hence within a broad class of lattice sieving algorithms covering almost all approaches to date, their asymptotic time complexity of $2^{0.292d + o(d)}$ is optimal. Similar conditional optimality results apply to lattice sieving variants, such as the $2^{0.265d + o(d)}$ complexity for quantum sieving [Laarhoven, PhD thesis 2016] and previously derived complexity estimates for tuple sieving [Herold-Kirshanova-Laarhoven, PKC 2018]. For the Hamming metric we derive new lower bounds for nearest neighbor searching which almost match the best upper bounds from the literature [May-Ozerov, Eurocrypt 2015]. As a consequence we derive conditional lower bounds on decoding attacks, showing that also here one should search for improvements elsewhere to significantly undermine security estimates from the literature.

Data and signal authentication schemes are being proposed to address Global Navigation Satellite Systems' (GNSS) vulnerability to spoofing. Due to the low power of their signals, the bandwidth available for authentication in GNSS is scarce. Since delayed-disclosure protocols, e.g., TESLA (timed-efficient stream loss-tolerant authentication), are efficient in terms of bandwidth and robust to signal impairments, they have been proposed and implemented by GNSS. The length of message authentication codes (MACs) and cryptographic keys are two crucial aspects of the protocol design as they have an impact on the utilized bandwidth, and therefore on the protocol performance. We analyze both aspects in detail for GNSS-TESLA and present recommendations for efficient yet safe MAC and key lengths. We further complement this analysis by proposing possible authentication success and failure policies and quantify the reduction of the attack surface resulting from employing them. The analysis shows that in some cases it is safe to use MAC and key sizes that are smaller than those proposed in best-practice guidelines. While some of our considerations are general to delayed-disclosure lightweight protocols for data and signal authentication, we particularize them for GNSS-TESLA protocols.

Fully homomorphic encryption (FHE) is one of the prospective tools for privacy-preserving machine learning (PPML), and several PPML models have been proposed based on various FHE schemes and approaches. Although the FHE schemes are known as suitable tools to implement PPML models, previous PPML models on FHE such as CryptoNet, SEALion, and CryptoDL are limited to only simple and non-standard types of machine learning models. These non-standard machine learning models are not proven efficient and accurate with more practical and advanced datasets. Previous PPML schemes replace non-arithmetic activation functions with simple arithmetic functions instead of adopting approximation methods and do not use bootstrapping, which enables continuous homomorphic evaluations. Thus, they could not use standard activation functions and could not employ a large number of layers. In this work, we firstly implement the standard ResNet-20 model with the RNS-CKKS FHE with bootstrapping and verify the implemented model with the CIFAR-10 dataset and the plaintext model parameters. Instead of replacing the non-arithmetic functions with the simple arithmetic function, we use state-of-the-art approximation methods to evaluate these non-arithmetic functions, such as the ReLU and softmax, with sufficient precision. Further, for the first time, we use the bootstrapping technique of the RNS-CKKS scheme in the proposed model, which enables us to evaluate an arbitrary deep learning model on the encrypted data. We numerically verify that the proposed model with the CIFAR-10 dataset shows 98.43% identical results to the original ResNet-20 model with non-encrypted data. The classification accuracy of the proposed model is 92.43%±2.65%, which is pretty close to that of the original ResNet-20 CNN model, 91.89%. It takes about 3 hours for inference on a dual Intel Xeon Platinum 8280 CPU (112 cores) with 172 GB memory. We think that it opens the possibility of applying the FHE to the advanced deep PPML model.

Because of the everlasting need of space to store even the headers of a blockchain, Ethereum requiring for example more than 4 GiB for such a task, superlight clients stood out as a necessity, for instance to enable deployment on wearable devices or smart contracts. Among them is FlyClient, whose main benefit was to be non-interactive. However, it is still to be shown how a such protocol can be deployed on an already existing chain, without contentious soft or hard forks. FlyClient suggests the use of velvet forks, a recently introduced mechanism for conflict-free deployment of blockchain consensus upgrades – yet the impact on the security of the light client protocol remains unclear. In this work, we provide a comprehensive analysis of the security of FlyClient under a velvet fork deployment. We discover that a naive velvet fork implementation exposes FlyClient to chain-sewing attacks, a novel type of attack, concurrently observed in similar superlight clients. Specifically, we show how an adversary subverting only a small fraction of the hash rate or consensus participants can not only execute doublespending attacks against velvet FlyClient nodes, but also print fake coins – with high probability of success. We then present three potential mitigations to this attack and prove their security both under velvet and, more traditional soft and hard fork deployment. In particular, our mitigations do not necessarily require a majority of honest, up-to-date miners.

As the Internet of Things (IoT) rolls out today to devices whose lifetime may well exceed a decade, conservative threat models should consider attackers with access to quantum computing power. The SUIT standard (specified by the IETF) defines a security architecture for IoT software updates, standardizing the metadata and the cryptographic tools---namely, digital signatures and hash functions---that guarantee the legitimacy of software updates. While the performance of SUIT has previously been evaluated in the pre-quantum context, it has not yet been studied in a post-quantum context. Taking the open-source implementation of SUIT available in RIOT as a case study, we overview post-quantum considerations, and quantum-resistant digital signatures in particular, focusing on low-power, microcontroller-based IoT devices which have stringent resource constraints in terms of memory, CPU, and energy consumption. We benchmark a selection of proposed post-quantum signature schemes (LMS, Falcon, and Dilithium) and compare them with current pre-quantum signature schemes (Ed25519 and ECDSA). Our benchmarks are carried out on a variety of IoT hardware including ARM Cortex-M, RISC-V, and Espressif (ESP32), which form the bulk of modern 32-bit microcontroller architectures. We interpret our benchmark results in the context of SUIT, and estimate the real-world impact of post-quantum alternatives for a range of typical software update categories.

Over the last few decades, the cost and difficulty of producing integrated circuits at ever shrinking node sizes has vastly increased, resulting in the manufacturing sector moving overseas. Using offshore foundries for chip fabrication, however, introduces new vulnerabilities into the design flow since there is little to no observability into the manufacturing process. At the same time, both design and optimization are becoming increasingly complex, particularly as SoC designs gain popularity. Common practices such as porting a design across node sizes and reusing cores at multiple area/performance tradeoffs further complicate assurance as layout specific features impede comparison. Methods have been developed for conducting integrated circuit decomposition on fabricated chips [1][2][16] to extract the as-fabricated design files such as the GDSII layout or gate-level netlist. While mature netlist equivalency checking tools are included with any design flow, there is a lack of tools for performing deeper analyses on the extracted designs for the purposes of hardware assurance or design recovery from obsolete parts. To this end, there is a need for a tool to extract functionality from netlists at a higher abstraction level to reconstruct behavioral Register Transfer Level (RTL) code.

While server-only authentication with certificates is the most widely used mode of operation for the Transport Layer Security (TLS) protocol on the world wide web, there are many applications where TLS is used in a different way or with different constraints. For example, embedded Internet-of-Things clients may have a server certificate pre-programmed and be highly constrained in terms of communication bandwidth or computation power. As post-quantum algorithms have a wider range of performance trade-offs, designs other than traditional ``signed-key-exchange'' may be worthwhile. The KEMTLS protocol, presented at ACM CCS 2020, uses key encapsulation mechanisms (KEMs) rather than signatures for authentication in the TLS 1.3 handshake, a benefit since most post-quantum KEMs are more efficient than PQ signatures. However, KEMTLS has some drawbacks, especially in the client authentication scenario which requires a full additional roundtrip. We explore how the situation changes with pre-distributed public keys, which may be viable in many scenarios, for example pre-installed public keys in apps, on embedded devices, cached public keys, or keys distributed out of band. Our variant of KEMTLS with pre-distributed keys, called KEMTLS-PDK, is more efficient in terms of both bandwidth and computation compared to post-quantum signed-KEM TLS (even cached public keys), and has a smaller trusted code base. When client authentication is used, KEMTLS-PDK is more bandwidth efficient than KEMTLS yet can complete client authentication in one fewer round trips, and has stronger authentication properties. Interestingly, using pre-distributed keys in KEMTLS-PDK changes the landscape on suitability of PQ algorithms: schemes where public keys are larger than ciphertexts/signatures (such as Classic McEliece and Rainbow) can be viable, and the differences between some lattice-based schemes is reduced. We also discuss how using pre-distributed public keys provides privacy benefits compared to pre-shared symmetric keys in TLS.

Attribute-based encryption (ABE) schemes by lattices are likely to resist quantum attacks, and can be widely applied to many Internet of Thing or cloud scenarios. One of the most attractive feature for ABE is the ability of fine-grained access control which provides an effective way to ensure data security. In this work, we propose an efficient ciphertext policy attribute-based encryption scheme based on hardness assumption of LWE. Being different from other similar schemes, a user's secret key can only be generated once only and it can be used to decrypt ciphertext under different access policies by making combinations of secret key fragments. Specially, we propose a method for binding users' secret keys with their attributes and identities, which solves the collusion attack problem. The security of the scheme is proved to be selective secure under the LWE assumption.

In this paper, we introduce the problem of Asynchronous Data Dissemination (ADD). Intuitively, an ADD protocol disseminates a message to all honest nodes in an asynchronous network, given that at least $t+1$ honest nodes initially hold the message where $t$ is the maximum number of malicious nodes. We design a simple and efficient ADD protocol for $n$ parties that is information-theoretically secure, tolerates up to one-third malicious nodes, and has a communication cost of $O(n|M|+n^2)$ for disseminating a message $M$. We then use our ADD protocol to improve many important primitives in cryptography and distributed computing. For asynchronous reliable broadcast (RBC), assuming collision-resistant hash functions, we give a RBC protocol with communication cost $O(n|M| + \kappa n^2)$ where $\kappa$ is the size of the hash function output. This improves over the prior best scheme with communication cost $O(n|M| + \kappa n^2 \log n)$ under the same setting. Our improved RBC protocol immediately improves the communication cost of asynchronous atomic broadcast and Asynchronous Distributed Key Generation~(ADKG) protocols. We also use our improved \rbc\ protocol along with additional new techniques to improve the communication cost of Asynchronous Verifiable Secret Sharing (AVSS), Asynchronous Complete Secret Sharing (ACSS), and dual-threshold \acss\ from $O(\kappa n^2 \log n)$ to $O(\kappa n^2)$ without using any trusted setup.

The proliferation of the Internet of Things (IoT) technology has made ubiquitous computing a reality by broadening Internet connectivity across diverse application domains, thus bridging billions of devices and human beings as well for information collection, data processing, and decision-making. In recent years, IoT technology and its applications in various industrial sectors have grown exponentially. Most existing industrial IoT (IIoT) implementations, however, are still relying on a centralized architecture, which is vulnerable to the single point of failure attack and requires a massive amount of computation at the central entity. The emerging blockchain technology is currently undergoing rapid development and has the full potential to revolutionize the IIoT platforms and applications. As a distributed and decentralized tamper-resistant ledger, blockchain maintains the consistency of data records at different locations and holds the potential to address the issues in traditional IIoT networks, such as heterogeneity, interoperability, and security. Integrating the blockchain technology into IIoT platforms requires to address several critical challenges that are inherent in IIoT and blockchain themselves, such as standardization, scalability, and interoperability. This paper provides a comprehensive review on the recent advances in architecture design and technology development towards tackling these challenges. We further provide several representative industrial use cases that can benefit from the integration of blockchain technology, and discuss the recent research trends and open issues in blockchain-enabled IIoT platforms.

The advent of blockchain protocols has reignited the interest in adaptively secure broadcast, as it is by now well understood that broadcasting over a diffusion network allows an adaptive adversary to corrupt the sender depending on the message it attempts to send and change it. Hirt and Zikas [Eurocrypt '10] proved that this is an inherent limitation of broadcast in the simulation-based setting---i.e., that this task is impossible against an adaptive adversary corrupting a strict majority of the parties (a task that is achievable against a static adversary). The contributions of this paper are two-fold. First, we show that, contrary to previous perception, the above limitation of adaptively secure broadcast is not an artifact of simulation-based security, but rather an inherent issue of adaptive security. In particular, we show that: (1) it also applies to the property-based broadcast definition adapted for adaptive adversaries, and (2) unlike other impossibilities in adaptive security, this impossibility cannot be circumvented by adding a programmable random oracle, in neither setting, property-based or simulation-based. Second, we turn to the resource-restricted cryptography (RRC) paradigm [Garay et al., Eurocrypt '20], which has proven useful in circumventing impossibility results, and ask whether it also affects the above negative result. We answer this question in the affirmative, by showing that time-lock puzzles (TLPs)---which can be viewed as an instance of RRC---indeed allow for achieving the property-based definition and circumvent the impossibility of adaptively secure broadcast. The natural question is then, do TLPs also allow for simulation-based adaptively secure broadcast against corrupted majorities? We answer this question in the negative. Nonetheless, we show that a positive result can be achieved via a non-committing analogue of TLPs in the programmable random-oracle model. Importantly, and as a contribution of independent interest, we also present the first (limited) composition theorem in the resource-restricted setting, which is needed for the complexity-based, non-idealized treatment of TLPs in the context of other protocols.

HMAC and NMAC are the most basic and important constructions to convert Merkle-Damgård hash functions into message authentication codes (MACs) or pseudorandom functions (PRFs). In the quantum setting, at CRYPTO 2017, Song and Yun showed that HMAC and NMAC are quantum pseudorandom functions (qPRFs) under the standard assumption that the underlying compression function is a qPRF. Their proof guarantees security up to $O(2^{n/5})$ or $O(2^{n/8})$ quantum queries when the output length of HMAC and NMAC is $n$ bits. However, there is a gap between the provable security bound and a simple distinguishing attack that uses $O(2^{n/3})$ quantum queries. This paper settles the problem of closing the gap. We show that the tight bound of the number of quantum queries to distinguish HMAC or NMAC from a random function is $\Theta(2^{n/3})$ in the quantum random oracle model, where compression functions are modeled as quantum random oracles. To give the tight quantum bound, based on an alternative formalization of Zhandry's compressed oracle technique, we introduce a new proof technique focusing on the symmetry of quantum query records.

Merkle tree is applied in diverse applications, namely, Blockchain, smart grid, IoT, Biomedical, financial transactions, etc., to verify authenticity and integrity. Also, the Merkle tree is used in privacy-preserving computing. However, the Merkle tree is a computationally costly data structure. It uses cryptographic string hash functions to partially verify the data integrity and authenticity of a data block. However, the verification process creates unnecessary network traffic because it requires partial hash values to verify a particular block. Moreover, the performance of the Merkle tree also depends on the network latency. Therefore, it is not feasible for most of the applications. To address the above issue, we proposed an alternative model to replace the Merkle tree, called HEX-BLOOM, and it is implemented using hash, Exclusive-OR and Bloom Filter. Our proposed model does not depends on network latency for verification of data block's authenticity and integrity. HEX-BLOOM uses an approximation model, Bloom Filter. Moreover, it employs a deterministic model for final verification of the correctness. In this article, we show that our proposed model outperforms the state-of-the-art Merkle tree in every aspect.

Abstract—This paper proposes the first side-channel attack on FALCON—a NIST Round-3 finalist for the post-quantum digital signature standard. We demonstrate a known-plaintext attack that uses the electromagnetic measurements of the device to extract the secret signing keys, which then can be used to forge signatures on arbitrary messages. The proposed attack targets the unique floating-point multiplications within FALCON’s Fast Fourier Transform through a novel extend-and-prune strategy that extracts the sign, mantissa, and exponent variables without false positives. The extracted floating-point values are then mapped back to the secret key’s coefficients. Our attack, notably, does not require pre-characterizing the power profile of the target device or crafting special inputs. Instead, the statistical differences on obtained traces are sufficient to successfully execute our proposed differential electromagnetic analysis. The results on an ARM-Cortex-M4 running the FALCON NIST’s reference software show that approximately 10k measurements are sufficient to extract the entire key.

Secure aggregation is a critical component in federated learning, which enables the server to learn the aggregate model of the users without observing their local models. Conventionally, secure aggregation algorithms focus only on ensuring the privacy of individual users in a single training round. We contend that such designs can lead to significant privacy leakages over multiple training rounds, due to partial user selection/participation at each round of federated learning. In fact, we empirically show that the conventional random user selection strategies for federated learning lead to leaking users' individual models within number of rounds linear in the number of users. To address this challenge, we introduce a secure aggregation framework with multi-round privacy guarantees. In particular, we introduce a new metric to quantify the privacy guarantees of federated learning over multiple training rounds, and develop a structured user selection strategy that guarantees the long-term privacy of each user (over any number of training rounds). Our framework also carefully accounts for the fairness and the average number of participating users at each round. We perform several experiments on MNIST and CIFAR-10 datasets in the IID and the non-IID settings to demonstrate the performance improvement over the baseline algorithms, both in terms of privacy protection and test accuracy.

We extend two-party private set union for secure computation, by considering matching between records having multiple identifiers (or keys), for example email and phone. In the classical setting of this problem, two parties want to perform various downstream computations on the union of two datasets. The union is computed by joining two datasets with the help of a single agreed upon identifier, say email. By extending this to joining records with multiple identifiers, we bring it much closer to real world uses where the match rate and match quality can be greatly improved by considering multiple identifiers. We introduce an extension to the Private-ID protocol [3] which outputs a full outer join (union) of two datasets by a match logic that can join rows containing multiple identifiers. We also introduce new techniques for privately sharding the protocol across multiple servers. Both constructions are based on Decisional Diffie–Hellman (DDH) assumptions.

The key exchange protocol that establishes initial shared secrets in the handshake of the Signal end-to-end encrypted messaging protocol has several important characteristics: (1) it runs asynchronously (without both parties needing to be simultaneously online), (2) it provides implicit mutual authentication while retaining deniability (transcripts cannot be used to prove either party participated in the protocol), and (3) it retains security even if some keys are compromised (forward secrecy and beyond). All of these properties emerge from clever use of the highly flexible Diffie--Hellman protocol. While quantum-resistant key encapsulation mechanisms (KEMs) can replace Diffie--Hellman key exchange in some settings, there is no KEM-based replacement for the Signal handshake that achieves all three aforementioned properties, in part due to the inherent asymmetry of KEM operations. In this paper, we show how to construct asynchronous deniable key exchange by combining KEMs and designated verifier signature (DVS) schemes. There are several candidates for post-quantum DVS schemes, either direct constructions or via ring signatures. This yields a template for an efficient post-quantum realization of the Signal handshake with the same asynchronicity and security properties as the original Signal protocol.

In the era of cloud computing and machine learning, data has become a highly valuable resource. Recent history has shown that the benefits brought forth by this data driven culture come at a cost of potential data leakage. Such breaches have a devastating impact on individuals and industry, and lead the community to seek privacy preserving solutions. A promising approach is to utilize Fully Homomorphic Encryption (FHE) to enable machine learning over encrypted data, thus providing resiliency against information leakage. However, computing over encrypted data incurs a high computational overhead, thus requiring the redesign of algorithms, in an ``FHE-friendly" manner, to maintain their practicality. In this work we focus on the ever-popular tree based methods (e.g., boosting, random forests), and propose a new privacy-preserving solution to training and prediction for trees. Our solution employs a low-degree approximation for the step-function together with a lightweight interactive protocol, to replace components of the vanilla algorithm that are costly over encrypted data. Our protocols for decision trees achieve practical usability demonstrated on standard UCI datasets encrypted with fully homomorphic encryption. In addition, the communication complexity of our protocols is independent of the tree size and dataset size in prediction and training, respectively, which significantly improves on prior works.

White-box cryptography has been proposed as a software protection technique for applications where limited or no hardware-based security is available. In recent years it has been crucial for enabling the security of mobile payment applications. In this paper we continue a recent line of research on device binding for white-box cryptography. Device binding ensures that a white-box program is only executable on one specific device and is unusable elsewhere. Building on this, we ask the following question: is it possible to design a {\em global} white-box program which is compiled once, but can be securely shared with multiple users and bound to each of their devices? Acknowledging this question, we define different flavours of security for such global white-boxes and provide corresponding constructions. We first consider families of \emph{strong} global white-boxes which can be securely distributed and bound to users' devices without the need of sharing secrets between the compiling entity and the users. We then show how such strong global white-boxes can be constructed based on message recoverable signatures (MRS). To this end, we introduce \emph{puncturable} MRS which we build based on puncturable PRFs and indistinguishability obfuscation. Later in the paper we consider the use of Token-Based Obfuscation (TBO) and show that TBO can provide us a direct way to construct global white-boxes, as long as we can securely share a token generation key between the users and compiling entities. While such global white-boxes have weaker security guarantees than their stronger counterparts, our results show that white-box crypto can be built from more accepted assumptions than previously considered. Moreover, TBO allows us to construct white-boxes for any functionality or encryption scheme and thus provides us a very general feasibility result for device binding.

Standardized Ethereum tokens, e.g., ERC-20 tokens, have become the norm in fundraising (through ICOs) and kicking off blockchain-based DeFi applications. However, they require the user’s wallet to hold both tokens and ether to pay the gas fee for making a transaction. This makes for a cumbersome and counterintuitive—at least for less tech-savvy users—user experience, especially when the token creator intends to switch to their own blockchain down the line, or wishes the flexibility of transferring the token to a different smart-contract enabled blockchain. We formalize, instantiate, and analyze in a composable manner a system that we call Etherless Ethereum Tokens (in short, EETs), which allows the token creator to allow its users to transact in a closed-economy manner, i.e., having only tokens on their wallet and paying any transaction fees in token units rather than gas. In the process, we devise a methodology for capturing Ethereum token-contracts in the Universal Composability (UC) framework, which can be of independent interest. We have implemented and benchmarked our system and compared it to another solution for obtaining similar functionality in Ethereum, i.e., the Gas Station Networks (GSN); in addition to being the first system with a rigorous security analysis, we demonstrate that EETs are not only far easier to deploy, but are also far less gas intensive than the GSN.

We study encrypted storage schemes where a client outsources data to an untrusted third-party server (such as a cloud storage provider) while maintaining the ability to privately query and dynamically update the data. We focus on encrypted multi-maps (EMMs), a structured encryption (STE) scheme that stores pairs of label and value tuples. EMMs allow queries on labels and return the associated value tuple. As responses are variable-length, EMMs are subject to volume leakage attacks introduced by Kellaris et al. [CCS’16]. To prevent these attacks, volume-hiding EMMs were introduced by Kamara and Moataz [Eurocrypt’19] that hide the label volumes (i.e., the value tuple lengths). As our main contribution, we present the first fully dynamic volume-hiding EMMs that are both asymptotically and concretely efficient. Furthermore, they are simultaneously forward and backward private which are the de-facto standard security notions for dynamic STE schemes. Additionally, we implement our schemes to showcase their concrete efficiency. Our experimental evaluations show that our constructions are able to add dynamicity with minimal to no additional cost compared to the prior best static volume-hiding schemes of Patel et al. [CCS’19].

We consider the task of learning a function via oracle queries, where the queries and responses are monitored (and perhaps also modified) by an untrusted intermediary. Our goal is twofold: First, we would like to prevent the intermediary from gaining any information about either the function or the learner's intentions (e.g. the particular hypothesis class the learner is considering). Second, we would like to curb the intermediary's ability to meaningfully interfere with the learning process, even when it can modify the oracles' responses. Inspired by the works of Ishai et al. (Crypto 2019) and Goldwasser et al. (ITCS 2021), we formalize two new learning models, called Covert Learning and Covert Verifiable Learning, that capture these goals. Then, assuming hardness of the Learning Parity with Noise (LPN) problem, we show: 1. Covert Learning algorithms in the agnostic setting for parity functions and decision trees, where a polynomial time eavesdropping adversary that observes all queries and responses learns nothing about either the function, or the learned hypothesis. 2. Covert Verifiable Learning algorithms that provide similar learning and privacy guarantees, even in the presence of a polynomial-time adversarial intermediary that can modify all oracle responses. Here the learner is granted additional random examples and is allowed to abort whenever the oracles responses are modified. Aside theoretical interest, our study is motivated by applications to the secure outsourcing of automated scientific discovery in drug design and molecular biology. It also uncovers limitations of current techniques for defending against model extraction attacks.

In this paper, we present three design flaws in the 802.11 standard that underpins Wi-Fi. One design flaw is in the frame aggregation functionality, and another two are in the frame fragmentation functionality. These design flaws enable an adversary to forge encrypted frames in various ways, which in turn enables exfiltration of sensitive data. We also discovered common implementation flaws related to aggregation and fragmentation, which further worsen the impact of our attacks. Our results affect all protected Wi-Fi networks, ranging from WEP all the way to WPA3, meaning the discovered flaws have been part of Wi-Fi since its release in 1997. In our experiments, all devices were vulnerable to one or more of our attacks, confirming that all Wi-Fi devices are likely affected. Finally, we present a tool to test whether devices are affected by any of the vulnerabilities, and we discuss countermeasures to prevent our attacks.

Designing Boolean functions whose output can be computed with light means at high speed, and satisfying all the criteria necessary to resist all major attacks on the stream ciphers using them as nonlinear components, has been an open problem since the beginning of this century, when algebraic attacks were invented. Functions allowing good resistance are known since 2008, but their output is too complex to compute. Functions with fast and easy to compute output are known which have good algebraic immunity, such as majority functions and the so-called hidden weight bit (HWB) functions, but they all have the same cryptographic weakness: their too small nonlinearity. \\In the present paper, we introduce a generalization of the HWB functions into a construction of $n$-variable balanced functions $f$ from $(n-1)$-variable Boolean functions $g$ having some property held by a large number of functions. Function $f$ is defined by its support, equal to the image set of a vectorial function depending on $g$. This makes the function complex enough for allowing good cryptographic parameters, while its output is light to compute. The HWB function is what we obtain with $f$ when the initial function $g$ equals constant 1. Other well chosen functions $g$ provide functions $f$ having good cryptographic parameters. \\We analyze the constructed functions $f$, we provide a fast way to compute their output, we determine their algebraic normal forms and we show that, most often, their algebraic degree is optimal. We study their Walsh transform and their nonlinearity and algebraic immunity. We observe with computer investigations that this generalization of the HWB function allows to keep its quality of being fast to compute and having good enough algebraic immunity, while significantly improving its nonlinearity. The functions already obtained in the investigations provide a quite good (and never reached before) trade-off between speed and security. Further (probably difficult) work should allow obtaining, among such generalized HWB functions whose number is huge, still better filter functions to be used in stream ciphers.

Despite intensive research on Boolean functions for cryptography for over thirty years, there are very few known general constructions allowing to satisfy all the necessary criteria for ensuring the resistance against all the main known attacks on the stream ciphers using them. In this paper, we investigate the general construction of Boolean functions $f$ from vectorial functions, in which the support of $f$ equals the image set of an injective vectorial function $F$, that we call a parameterization of $f$. Any Boolean function whose Hamming weight is a power of 2, and in particular, every balanced Boolean function, can be obtained this way. We study five illustrations of this general construction. The three first correspond to known classes of functions (Maiorana-McFarland, majority functions and balanced functions in odd numbers of variables with optimal algebraic immunity). The two last correspond to new classes of Boolean functions: - sums of indicators of disjoint graphs of $(k,n-k$)-functions, - functions parameterized by highly nonlinear injective vectorial $(n-1,n)$-functions derived from functions due to Beelen and Leander. We study the cryptographic parameters (corresponding to the main criteria) of balanced Boolean functions, according to those of their parameterizations: the algebraic degree of $f$, that we relate to the algebraic degrees of $F$ and of its graph indicator, the nonlinearity of $f$, that we relate by a bound to the nonlinearity of $F$, and the algebraic immunity (AI), whose optimality is related to a natural question in linear algebra, and which may be handled (in two ways) by means of the graph indicator of $F$. We show how the algebraic degree and the nonlinearity of the parameterized function can be controlled. We revisit each of the five classes for each criterion. We show that the fourth class is very promising, thanks to a lower bound on the nonlinearity by means of the nonlinearity of the chosen $(k,n-k$)-functions. Its sub-class made of the sums of indicators of affine functions, for which we prove an upper bound on the nonlinearity, seems also interesting. The fifth class includes functions with optimal algebraic degree, good nonlinearity and good AI. We leave for future works the determination of simple effective sufficient conditions on $F$ ensuring that $f$ has a good AI, the completion of the study of the fourth class, the mathematical study of the AI and fast algebraic immunity of the functions in the fifth class, and the introduction and study of a class of parameterized functions having good parameters and whose output is fast to compute.

CryptoNote blockchains like Monero represent the largest public deployments of linkable ring signatures. Beginning with the work of Kumar et al. (ESORICS 2017) and Möser et al. (PoPETs 2018), several techniques have been proposed to trace CryptoNote transactions, i.e. identify the actual signing key, by using the transaction history. Yu et al. (FC 2019) introduced the closed set attack for undeniable traceability and proved that it is optimal by showing that it has the same performance as the brute-force attack. However, they could only implement an approximation of the closed set attack due to its exponential time complexity. In this paper, we show that the Dulmage-Mendelsohn (DM) decomposition of bipartite graphs gives a polynomial-time implementation of the closed set attack. Our contribution includes open source implementations of the DM decomposition and the clustering algorithm (the approximation to the closed set attack proposed by Yu et al). Using these implementations, we evaluate the empirical performance of these methods on the Monero dataset in two ways -- firstly using data only from the main Monero chain and secondly using data from four hard forks of Monero in addition to the main Monero chain. We have released the scripts used to perform the empirical analysis along with step-by-step instructions.

Many organizations need large amounts of high-quality data for their applications, and one way to acquire such data is to combine datasets from multiple parties. Since these organizations often own sensitive data that cannot be shared in the clear with others due to policy regulation and business competition, there is increased interest in utilizing secure multi-party computation (MPC). MPC allows multiple parties to jointly compute a function without revealing their inputs to each other. We present Cerebro, an end-to-end collaborative learning platform that enables parties to compute learning tasks without sharing plaintext data. By taking an end-to-end approach to the system design, Cerebro allows multiple parties with complex economic relationships to safely collaborate on machine learning computation through the use of release policies and auditing, while also enabling users to achieve good performance without manually navigating the complex performance tradeoffs between MPC protocols.

We study a quantum cryptography based on an algorithm for determining simultaneously all the mappings of a Boolean function using an entangled state. The security of our cryptography is based on the Ekert 1991 protocol, which uses an entangled state. Eavesdropping destroys the entanglement. Alice selects a secret function from the number of possible function types. Bob's aim is then to determine the selected function (a key) without an eavesdropper learning it. In order for both Alice and Bob to be able to select the same function classically, in the worst case Bob requires multiple queries to Alice. In the quantum case however, Bob requires just a single query. By measuring the single entangled state, which is sent to him by Alice, Bob can obtain the function that Alice selected. This quantum key distribution method is faster compared to the multiple queries that would be required in the classical case.

In this paper, we study the dual of generalized bent functions $f: V_{n}\rightarrow \mathbb{Z}_{p^k}$ where $V_{n}$ is an $n$-dimensional vector space over $\mathbb{F}_{p}$ and $p$ is an odd prime, $k$ is a positive integer. It is known that weakly regular generalized bent functions always appear in pairs since the dual of a weakly regular generalized bent function is also a weakly regular generalized bent function. The dual of non-weakly regular generalized bent functions can be generalized bent or not generalized bent. By generalizing the construction of \cite{Cesmelioglu5}, we obtain an explicit construction of generalized bent functions for which the dual can be generalized bent or not generalized bent. We show that the generalized indirect sum construction method given in \cite{Wang} can provide a secondary construction of generalized bent functions for which the dual can be generalized bent or not generalized bent. By using the knowledge on ideal decomposition in cyclotomic field, we prove that $f^{**}(x)=f(-x)$ if $f$ is a generalized bent function and its dual $f^{*}$ is also a generalized bent function. For any non-weakly regular generalized bent function $f$ which satisfies that $f(x)=f(-x)$ and its dual $f^{*}$ is generalized bent, we give a property and as a consequence, we prove that there is no self-dual generalized bent function $f: V_{n}\rightarrow \mathbb{Z}_{p^k}$ if $p\equiv 3 \ (mod \ 4)$ and $n$ is odd. For $p \equiv 1 \ (mod \ 4)$ or $p\equiv 3 \ (mod \ 4)$ and $n$ is even, we give a secondary construction of self-dual generalized bent functions. In the end, we characterize the relations between the generalized bentness of the dual of generalized bent functions and the bentness of the dual of bent functions, as well as the self-duality relations between generalized bent functions and bent functions by the decomposition of generalized bent functions.

Today's side channel attack targets are often complex devices in which instructions are processed in parallel and work on 32-bit data words. Consequently, the state that is involved in producing leakage in these modern devices is large, and basing evaluations (i.e. worst case attacks), simulators, and assumptions for (masking) countermeasures on a potentially incomplete state can lead to drastically wrong conclusions. We put forward a novel notion for the ``completeness'' of an assumed state, together with an efficient statistical test that is based on ``collapsed models''. Our novel test can be used to recover a state that contains multiple 32-bit variables in a grey box setting. We illustrate how our novel test can help to guide side channel attacks and we reveal new attack vectors for existing implementations. We also show how the application of our statistical test shows where even the most recent leakage simulators do not capture all available leakage of their respective target devices.

Mixing arithmetic and boolean circuits to perform privacy-preserving machine learning has become increasingly popular. Towards this, we propose a framework for the case of four parties with at most one active corruption called Tetrad. Tetrad works over rings and supports two levels of security, fairness and robustness. The fair multiplication protocol costs 5 ring elements, improving over the state-of-the-art Trident (Chaudhari et al. NDSS'20). A key feature of Tetrad is that robustness comes for free over fair protocols. Other highlights across the two variants include (a) probabilistic truncation without overhead, (b) multi-input multiplication protocols, and (c) conversion protocols to switch between the computational domains, along with a tailor-made garbled circuit approach. Benchmarking of Tetrad for both training and inference is conducted over deep neural networks such as LeNet and VGG16. We found that Tetrad is up to 4 times faster in ML training and up to 5 times faster in ML inference. Tetrad is also lightweight in terms of deployment cost, costing up to 6 times less than Trident.

Most existing Secure Multi-Party Computation (MPC) protocols for privacy-preserving training of decision trees over distributed data assume that the features are categorical. In real-life applications, features are often numerical. The standard ``in the clear'' algorithm to grow decision trees on data with continuous values requires sorting of training examples for each feature in the quest for an optimal cut-point in the range of feature values in each node. Sorting is an expensive operation in MPC, hence finding secure protocols that avoid such an expensive step is a relevant problem in privacy-preserving machine learning. In this paper we propose three more efficient alternatives for secure training of decision tree based models on data with continuous features, namely: (1) secure discretization of the data, followed by secure training of a decision tree over the discretized data; (2) secure discretization of the data, followed by secure training of a random forest over the discretized data; and (3) secure training of extremely randomized trees (``extra-trees'') on the original data. Approaches (2) and (3) both involve randomizing feature choices. In addition, in approach (3) cut-points are chosen randomly as well, thereby alleviating the need to sort or to discretize the data up front. We implemented all proposed solutions in the semi-honest setting with additive secret sharing based MPC. In addition to mathematically proving that all proposed approaches are correct and secure, we experimentally evaluated and compared them in terms of classification accuracy and runtime. We privately train tree ensembles over data sets with 1000s of instances or features in a few minutes, with accuracies that are at par with those obtained in the clear. This makes our solution orders of magnitude more efficient than the existing approaches, which are based on oblivious sorting.

Cellular networks connect nearly every human on the planet; they consequently have visibility into location data and voice, SMS, and data contacts and communications. Such near-universal visibility represents a significant threat to the privacy of mobile subscribers. In 5G networks, end-user mobile device manufacturers assign a Permanent Equipment Identifier (PEI) to every new device. Mobile operators legitimately use the PEI to blocklist stolen devices from the network to discourage device theft, but the static PEI also provides a mechanism to uniquely identify and track subscribers. Advertisers and data brokers have also historically abused the PEI for data fusion of location and analytics data, including private data sold by cellular providers. In this paper, we present a protocol that allows mobile devices to prove that they are not in the blocklist without revealing their PEI to any entity on the network. Thus, we maintain the primary purpose of the PEI while preventing potential privacy violations. We describe provably secure anonymous proof of blocklist non-membership for cellular network, based on the RSA accumulators and zero-knowledge proofs introduced by Camenisch and Lysyanskaya (Crypto'02) and expanded upon by Li, Li and Xue (ACNS'07). We show experimentally that this approach is viable for cellular networks: a phone can create a blocklist non-membership proof in only 3432 milliseconds of online computation, and the network can verify the proof in less than one second on average. In total this adds fewer than 4.5 seconds to the rare network attach process. This work shows that PEIs can be attested anonymously in 5G and future network generations, and it paves the way for additional advances toward a cellular network with guaranteed privacy.

We give a quantum reduction from finding short codewords in a random linear code to decoding for the Hamming metric. This is the first time such a reduction (classical or quantum) has been obtained. Our reduction adapts to linear codes Stehlé-Steinfield-Tanaka-Xagawa’ re-interpretation of Regev's quantum reduction from finding short lattice vectors to solving the Closest Vector Problem. The Hamming metric is a much coarser metric than the Euclidean metric and this adaptation has needed several new ingredients to make it work. For instance, in order to have a meaningful reduction it is necessary in the Hamming metric to choose a very large decoding radius and this needs in many cases to go beyond the radius where decoding is always unique. Another crucial step for the analysis of the reduction is the choice of the errors that are being fed to the decoding algorithm. For lattices, errors are usually sampled according to a Gaussian distribution. However, it turns out that the Bernoulli distribution (the analogue for codes of the Gaussian) is too much spread out and cannot be used, as such, for the reduction with codes. This problem was solved by using instead a truncated Bernoulli distribution.

Properties of the Grain-128AEAD key re-introduction, as part of the cipher initialization, are analyzed and discussed. We consider and analyze several possible alternatives for key re-introduction and identify weaknesses, or potential weaknesses, in them. Our results show that it seems favorable to separate the state initialization, the key re-introduction, and the $A/R$ register initialization into three separate phases. Based on this, we propose a new cipher initialization and update the cipher version to Grain-128AEADv2. It can be noted that previously reported and published analysis of the cipher remains valid also for this new version.

Zero-knowledge proofs are highly flexible cryptographic protocols that are an important building block for many secure systems. Typically, these are defined with respect to statements that are formulated as arithmetic operations over a fixed finite field. This inflexibility is a disadvantage when it comes to complex programs, as some fields are more amenable to express certain operations than others. At the same time, there do not seem to be many proofs with a programming model similar to those found in modern computer architectures that perform arithmetic with 32 or 64 bit integers. In this work, we present solutions to both of these problems. First, we show how to efficiently check consistency of secret values between different instances of zero-knowledge protocols based on the commit-and-prove paradigm. This allows a protocol user to easily switch to the most efficient representation for a given task. To achieve this, we modify the extended doubly-authenticated bits (edabits) approach by Escudero et al. (Crypto 2020), originally developed for MPC, and optimize it for the zero-knowledge setting. As an application of our consistency check, we also introduce protocols for efficiently verifying truncations and comparisons of shared values both modulo a large prime $p$ and modulo $2^k$. Finally, we complement our conversion protocols with new protocols for verifying arithmetic statements in $\mathbb{Z}_{2^k}$. Here, we build upon recent interactive proof systems based on information-theoretic MACs and vector oblivious linear evaluation (VOLE), and show how this paradigm can be adapted to the ring setting. In particular, we show that supporting such modular operations natively in a proof system can be almost as efficient as proofs over large fields or bits, and this also easily plugs into our framework for zero-knowledge conversions.

We describe a garbling scheme for boolean circuits, in which XOR gates are free and AND gates require communication of $1.5\kappa + 5$ bits. This improves over the state-of-the-art "half-gates" scheme of Zahur, Rosulek, and Evans (Eurocrypt 2015), in which XOR gates are free and AND gates cost $2\kappa$ bits. The half-gates paper proved a lower bound of $2\kappa$ bits per AND gate, in a model that captured all known garbling techniques at the time. We bypass this lower bound with a novel technique that we call slicing and dicing, which involves slicing wire labels in half and operating separately on those halves. Ours is the first to bypass the lower bound while being fully compatible with free-XOR, making it a drop-in replacement for half-gates. Our construction is proven secure from a similar assumption to prior free-XOR garbling (circular correlation-robust hash), and uses only slightly more computation than half-gates.

Cleve’s celebrated lower bound (STOC’86) showed that a de facto strong fairness notion is impossible in 2-party coin toss, i.e., the corrupt party always has a strategy of biasing the honest party’s outcome by a noticeable amount. Nonetheless, Blum’s famous coin-tossing protocol(CRYPTO’81) achieves a strictly weaker “game-theoretic” notion of fairness — specifically, it is a 2-party coin toss protocol in which neither party can bias the outcome towards its own preference; and thus the honest protocol forms a Nash equilibrium in which neither party would want to deviate. Surprisingly, an n-party analog of Blum’s famous coin toss protocol was not studied till recently. The elegant work by Chung et al. was the first to explore the feasibility of game-theoretically fair n-party coin toss in the presence of corrupt majority. We may assume that each party has a publicly stated preference for either the bit 0 or 1, and if the outcome agrees with the party’s preference, it obtains utility 1; else it obtains nothing.A natural game-theoretic formulation is to require that the honest protocol form a coalition-resistant Nash equilibrium, i.e., no coalition should have incentive to deviate from the honest behavior. Chung et al. phrased this game-theoretic notion as “cooperative-strategy-proofness”or “CSP-fairness” for short. Unfortunately, Chung et al. showed that under (n-1)-sized coalitions, it is impossible to design such a CSP-fair coin toss protocol, unless all parties except one prefer the same bit.In this paper, we show that the impossibility of Chung et al. is in fact not as broad as it may seem. When coalitions are majority but not n-1 in size, we can indeed get feasibility results in some meaningful parameter regimes. We give a complete characterization of the regime in whichCSP-fair coin toss is possible, by providing a matching upper- and lower-bound. Our complete characterization theorem also shows that the mathematical structure of game-theoretic fairness is starkly different from the de facto strong fairness notion in the multi-party computation literature.

A dominant approach to solving the scalability problem in blockchain systems has been the development of layer 2 protocols and in particular payment channel networks (PCNs) such as the Bitcoin Lightning Network (LN). Routing payments over LN requires the coordination of all path intermediaries in a multi-hop round trip that encumbers the layer 2 solution both in terms of responsiveness as well as privacy. The issue is resolved by virtual channel protocols that, capitalizing on a suitable off-chain setup operation, enable the two endpoints to engage as if they had a direct payment channel between them. Once the channel is not needed anymore, it can be optimistically closed in an off-chain fashion. Apart from communication efficiency, virtual channel constructions have three natural desiderata. A virtual channel constructor is recursive if it can also be applied on pre-existing virtual channels, variadic if it can be applied on any number of pre-existing channels, and symmetric if it imposes equitable costs on all channel participants in every execution scenario. We introduce Elmo, the first Bitcoin-suitable recursive variadic virtual channel construction. Furthermore our virtual channel constructor is symmetric and offers optimal round complexity for payments, optimistic closing and unilateral closing. We express and prove the security of our construction in the universal composition setting, using a novel induction-based proof technique of independent interest. As an additional contribution, we implement a flexible simulation framework for on- and off-chain payments and compare the efficiency of Elmo with previous virtual channel constructors.

Field Programmable Gate Arrays (FPGAs) used as hardware accelerators in the cloud domain allow end-users to accelerate their custom applications while ensuring minimal dynamic power consumption. Cloud infrastructures aim to maximize profit by achieving optimized resource sharing among its cloud users. However, the FPGAs' reconfigurable nature poses unique security and privacy challenges in a shared cloud environment. In this paper, we aim to understand the interactions between FPGA and the host servers on the cloud to analyze FaaS platforms' security. We propose a vulnerability taxonomy based on the runtime attributes of the FaaS platforms. The taxonomy aims to assist the identification of critical sources of vulnerabilities in the platform in allowing focused security verification. We demonstrate the proof-of-concept by characterizing the potential source of vulnerabilities in the Stratix-10 FaaS platforms. We then focused on only one major source to perform more focused verification. The proof-of-concept is demonstrated by identifying the potential source of vulnerabilities in the Stratix-10 FaaS platforms. Then, to conduct more focused verification, we narrowed our focus to only one major source. It aided in the identification of several low-level software vulnerabilities. The discovered vulnerabilities could be remotely exploited to cause denial-of-service and information leakage attacks. The concerned entities have released software updates to address the vulnerabilities.

Following the pioneering work of Boneh and Franklin (CRYPTO '01), the challenge of constructing an identity-based encryption scheme based on the Diffie-Hellman assumption remained unresolved for more than 15 years. Evidence supporting this lack of success was provided by Papakonstantinou, Rackoff and Vahlis (ePrint '12), who ruled out the existence of generic-group identity-based encryption schemes supporting an identity space of sufficiently large polynomial size. Nevertheless, the breakthrough result of D{ö}ttling and Garg (CRYPTO '17) settled this long-standing challenge via a non-generic construction. We prove a tight impossibility result for generic-group identity-based encryption, ruling out the existence of any non-trivial construction: We show that any scheme whose public parameters include $n_{\sf pp}$ group elements may support at most $n_{\sf pp}$ identities. This threshold is trivially met by any generic-group public-key encryption scheme whose public keys consist of a single group element (e.g., ElGamal encryption). In the context of algebraic constructions, generic realizations are often both conceptually simpler and more efficient than non-generic ones. Thus, identifying exact thresholds for the limitations of generic groups is not only of theoretical significance but may in fact have practical implications when considering concrete security parameters.

In this paper, we introduce a new method to prove the knowledge of an isogeny of given degree between two supersingular elliptic curves. Our approach can be extended to verify the evaluation of the secret isogeny on some points of the domain. The main advantage of this new proof of knowledge is its compactness which is orders of magnitude better than existing proofs of isogeny knowledge. The principle of our method is to reveal some well-chosen endomorphisms and does not constitute a zero-knowledge proof. However, when the degree is a large prime, we can introduce a new hardness assumption upon which we build the first verifiable random function (VRF) based on isogenies. Our protocol can be seen as a generalization of the BLS-style classical construction from elliptic curves and achieves one-time pseudo-randomness in the random oracle model. We propose concrete parameters for this new scheme which reach post-quantum NIST-1 level of security. Our VRF has an overall cost (proof size, key size and output size) of roughly $1$KB, which is shorter than all the other post-quantum instantiations based on lattices. In the process, we also develop several algorithmic tools to solve norm equations over quaternion orders that may be of independent interest.

We propose Manta, a plug and play private DeFi stack that consists of MantaDAP, a multi-asset decentralized anonymous payment scheme and MantaDAX, an automated market maker(AMM) based decentralized anonymous exchange scheme. Compared with existing privacy preserving cryptocurrencies such as Zcash and Monero,Manta supports multiple base assets and allows the privatized assets to be exchanged anonymously via MantaDAX. We think this is a major step forward towards building a privacy preserving DeFi stack. Thanks to the efficiency of modern NIZKs (non-interactive zero-knowledge proof systems) and our carefully crafted design,Manta is efficient: our benchmarks reports a 15 second, off-line zero-knowledge proof (ZKP) generation time, and a 6 millisecond, on-line proof verification time.

Proof-of-Stake (PoS) distributed ledgers are the most common alternative to Bitcoin’s Proof-of-Work (PoW) paradigm, replacing the hardware dependency with stake, i.e., assets that a party controls. Similar to PoW’s mining pools, PoS’s stake pools, i.e., collaborative entities comprising of multiple stakeholders, allow a party to earn rewards more regularly, compared to participating on an individual basis. However, stake pools tend to increase centralization, since they are typically managed by a single party that acts on behalf of the pool’s members. In this work we propose Conclave, a formal design of a Collective Stake Pool, i.e., a decentralized pool with no single point of authority. We formalize Conclave as an ideal functionality and implement it as a distributed protocol, based on standard cryptographic primitives. Among Conclave’s building blocks is a weighted threshold signature scheme (WTSS); to that end, we define a WTSS ideal functionality — which might be of independent interest — and propose two constructions based on threshold ECDSA, which enable (1) fast trustless setup and (2) identifiable aborts.

This short note shows that NTRU in NIST PQC Round~3 finalist is anonymous in the QROM if the underlying NTRU PKE is strongly disjoint-simulatable and a hybrid PKE scheme constructed from NTRU as KEM and appropriate DEM is anonymous and robust. This solves the open problem to investigate anonymity and robustness of NTRU posed by Grubbs, Maram, and Paterson (Cryptography ePrint Archive 2021/708).

The Boneh-Katz transformation (CT-RSA 2005) converts a selectively-secure identity/tag-based encryption scheme into a public-key encryption scheme secure against chosen-ciphertext attacks. We show that if the underlying primitives are pseudorandom, then the public-key encryption scheme obtained by the Boneh-Katz transformation is also pseudorandom. A similar result holds for oblivious sampleability (Canetti and Fischlin (CRYPTO 2001)). As applications, we can construct * pseudorandom and obliviously-samplable public-key encryption schemes from lattices and codes, * universally-composable non-interactive bit-commitment from lattices, * public-key steganography which is steganographically secure against adaptive chosen-covertext attacks and steganographic key-exchange from lattices and codes, * anonymous authenticated key exchange from lattices and codes, * public-key encryption secure against simulation-based, selective-opening chosen-ciphertext attacks from lattices and codes.

A garbling scheme is a fundamental cryptographic building block with a long list of applications. The study of different techniques for garbling a function, towards optimizing computation and communication complexity, has been an area of active research. Most common garbling techniques work by representing each gate in the circuit as a set of ciphertexts that encrypt its truth table row-by-row. In this work we present a new garbling scheme in the random oracle (RO) model that garbles circuits in the gate-by-gate paradigm by capturing the gate functionality (AND, XOR) as a whole rather than as a set of ciphertexts. The final gate garbling requires $4\kappa$ bits of communication in expectation, 4 RO calls for garbling and 1 RO call for evaluation. We prove that the scheme satisfies privacy in the non-programmable random oracle model and against PPT adversaries. We also show how this scheme can be extended to support free-XOR and garble any gate functionality over binary inputs.

The existence of one-way functions implies secure digital signatures, but not public-key encryption (at least in a black-box setting). Somewhat surprisingly, though, efficient public-key encryption schemes appear to be much easier to construct from concrete algebraic assumptions (such as the factoring of Diffie-Hellman-like assumptions) than efficient digital signature schemes. In this work, we provide one reason for this apparent difficulty to construct efficient signature schemes. Specifically, we prove that a wide range of algebraic signature schemes (in which verification essentially checks a number of linear equations over a group) fall to conceptually surprisingly simple linear algebra attacks. In fact, we prove that in an algebraic signature scheme, sufficiently many signatures can be linearly combined to a signature of a fresh message. We present attacks both in known-order and hidden-order groups (although in hidden-order settings, we have to restrict our definition of algebraic signatures a little). More explicitly, we show: - the insecurity of all algebraic signature schemes in Maurer's generic group model (in pairing-free groups), as long as the signature schemes do not rely on other cryptographic assumptions, such as hash functions. - the insecurity of a natural class of signatures in hidden-order groups, where verification consists of linear equations over group elements. We believe that this highlights the crucial role of public verifiability in digital signature schemes. Namely, while public-key encryption schemes do not require any publicly verifiable structure on ciphertexts, it is exactly this structure on signatures that invites attacks like ours and makes it hard to construct efficient signatures.

GIFT-COFB is a finalist of NIST Lightweight cryptography project that aims at standardizing authenticated encryption schemes for constrained devices. It is a block cipher-based scheme and comes with a provable security result. This paper studies the tightness of the provable security bounds of GIFT-COFB, which roughly tells that, if instantiated by a secure $n$-bit block cipher, we need $2^{n/2}$ encrypted blocks or $2^{n/2}/n$ decryption queries to break the scheme. This paper shows that the former condition is indeed tight, by presenting forgery attacks that work with $2^{n/2}$ encrypted blocks with single decryption query. This fills the missing spot of previous attacks presented by Khairallah, and confirms the tightness of the security bounds with respect to encryption. We remark that our attacks work independent of the underlying block cipher.

Machine Learning (ML) algorithms, especially deep neural networks (DNN), have proven themselves to be extremely useful tools for data analysis, and are increasingly being deployed in systems operating on sensitive data, such as recommendation systems, banking fraud detection, and healthcare systems. This underscores the need for privacy-preserving ML (PPML) systems, and has inspired a line of research into how such systems can be constructed efficiently. We contribute to this line of research by proposing a framework that allows efficient and secure evaluation of full-fledged state-of-the-art ML algorithms via secure multi-party computation (MPC). This is in contrast to most prior works on PPML, which require advanced ML algorithms to be substituted with approximated variants that are ``MPC-friendly'', before MPC techniques are applied to obtain a PPML algorithm. A drawback of the latter approach is that it requires careful fine-tuning of the combined ML and MPC algorithms, and might lead to less efficient algorithms or inferior quality ML (such as lower prediction accuracy). This is an issue for secure training of DNNs in particular, as this involves several arithmetic algorithms that are thought to be ``MPC-unfriendly'', namely, integer division, exponentiation, inversion, and square root extraction. In this work, we propose secure and efficient protocols for the above seemingly MPC-unfriendly computations (but which are essential to DNN). Our protocols are three-party protocols in the honest-majority setting, and we propose both passively secure and actively secure with abort variants. A notable feature of our protocols is that they simultaneously provide high accuracy and efficiency. This framework enables us to efficiently and securely compute modern ML algorithms such as Adam (Adaptive moment estimation) and the softmax function ``as is'', without resorting to approximations. As a result, we obtain secure DNN training that outperforms state-of-the-art three-party systems; our \textit{full} training is up to $6.7$ times faster than just the \textit{online} phase of the recently proposed FALCON (Wagh et al. at PETS'21) on the standard benchmark network for secure training of DNNs. To further demonstrate the scalability of our protocols, we perform measurements on real-world DNNs, AlexNet and VGG16, which are complex networks containing millions of parameters. The performance of our framework for these networks is up to a factor of about $12\sim 14$ faster for AlexNet and $46\sim 48$ faster for VGG16 to achieve an accuracy of $70\%$ and $75\%$, respectively, when compared to FALCON.

We study masking countermeasures for side-channel attacks against signature schemes constructed from the MPC-in-the-head paradigm, specifically when the MPC protocol uses preprocessing. This class of signature schemes includes Picnic, an alternate candidate in the third round of the NIST post-quantum standardization project. The only previously known approach to masking MPC-in-the-head signatures suffers from interoperability issues and increased signature sizes. Further, we present a new attack to demonstrate that known countermeasures are not sufficient when the MPC protocol uses a preprocessing phase, as in Picnic3. We overcome these challenges by showing how to mask the underlying zero-knowledge proof system due to Katz--Kolesnikov--Wang (CCS 2018) for any masking order, and by formally proving that our approach meets the standard security notions of non-interference for masking countermeasures. As a case study, we apply our masking technique to Picnic. We then implement different masked versions of Picnic signing providing first order protection for the ARM Cortex M4 platform, and quantify the overhead of these different masking approaches. We carefully analyze the side-channel risk of hashing operations, and give optimizations that reduce the CPU cost of protecting hashing in Picnic by a factor of five. The performance penalties of the masking countermeasures ranged from 1.8 to 5.5, depending on the degree of masking applied to hash function invocations.

We provide three first-order hardware maskings of the AES, each allowing for a different trade-off between the number of shares and the number of register stages. All maskings use a generalization of the changing of the guards method enabling the re-use of randomness between masked S-boxes. As a result, the maskings do not require fresh randomness while still allowing for a minimal number of shares and providing provable security in the glitch-extended probing model. The low-area variant has five cycles of latency and a serialized area cost of $8.13~kGE$. The low-latency variant reduces the latency to three cycles while increasing the serialized area by $67.89\%$ compared to the low-area variant. The maskings of the AES encryption are implemented on FPGA and evaluated with Test Vector Leakage Assessment (TVLA).

We present a framework GenoPPML for privacy-preserving machine learning in the context of sensitive genomic data processing. The technology combines secure multiparty computation techniques based on the recently proposed Manticore secure multiparty computation framework for model training and fully homomorphic encryption based on TFHE for model inference. The framework was successfully used to solve breast cancer prediction problems on gene expression datasets coming from distinct private sources while preserving their privacy - the solution winning 1st place for both Tracks I and III of the genomic privacy competition iDASH'2020. Extensive benchmarks and comparisons to existing works are performed. Our 2-party logistic regression computation is $11\times$ faster than the one in De Cock et al. on the same dataset and it uses only a single CPU core.

In this paper, we present preimage attacks on 4-round Keccak-224/256 as well as 4-round Keccak[$r = 640,c = 160,l = 80$] in the preimage challenges. We revisit the Crossbred algorithm for solving the Boolean multivariate quadratic (MQ) system, propose a new view for the case $D = 2$ and elaborate the computational complexity. The result shows that the Crossbred algorithm outperforms brute force theoretically and practically with feasible memory costs. In our attacks, we construct Boolean MQ systems in order to make full use of variables. With the help of solving MQ systems, we successfully improve preimage attacks on Keccak-224/256 reduced to 4 rounds. Moreover, we implement the preimage attack on 4-round Keccak[$r = 640,c = 160,l = 80$], an instance in the Keccak preimage challenges, and find 78-bit matched \textit{near preimages}. Due to the fundamental rule of solving MQ systems, the complexity elaboration of Crossbred algorithm is of independent interest.

The idea of hybrid homomorphic encryption (HHE) is to drastically reduce bandwidth requirements when using homomorphic encryption (HE) at the cost of more expensive computations in the encrypted domain. To this end, various dedicated schemes for symmetric encryption have already been proposed. However, it is still unclear if those ideas are already practically useful, because (1) no cost-benefit analysis was done for use cases and (2) very few implementations are publicly available. We address this situation in several ways. We build an open-source benchmarking framework involving several use cases covering three popular libraries. Using this framework, we explore properties of the respective HHE proposals. It turns out that even medium-sized use cases are infeasible, especially when involving integer arithmetic. Next, we propose Pasta, a cipher thoroughly optimized for integer HHE use cases. Pasta is designed to minimize the multiplicative depth, while also leveraging the structure of two state-of-the-art integer HE schemes (BFV and BGV) to minimize the homomorphic evaluation latency. Using our new benchmarking environment, we extensively evaluate Pasta in SEAL and HElib and compare its properties to 8 existing ciphers in two use cases. Our evaluations show that Pasta outperforms its competitors for HHE both in terms of homomorphic evaluation time and noise consumption, showing its efficiency for applications in real-world HE use cases. Concretely, Pasta outperforms Agrasta by a factor of up to 82, Masta by a factor of up to 6 and Hera up to a factor of 11 when applied to the two use cases.

Recent progress in interactive zero-knowledge (ZK) proofs has improved the efficiency of proving large-scale computations significantly. Nevertheless, real-life applications (e.g., in the context of private inference using deep neural networks) often involve highly complex computations, and existing ZK protocols lack the expressiveness and scalability to prove results about such computations efficiently. In this paper, we design, develop, and evaluate a ZK system (Mystique) that allows for efficient conversions between arithmetic and Boolean values, between publicly committed and privately authenticated values, and between fixed-point and floating-point numbers. Targeting large-scale neural-network inference, we also present an improved ZK protocol for matrix multiplication that yields a 7× improvement compared to the state-of-the-art. Finally, we incorporate Mystique in Rosetta, a TensorFlow-based privacy-preserving framework. Mystique is able to prove correctness of an inference on a private image using a committed (private) ResNet-101 model in 28 minutes, and can do the same task when the model is public in 5 minutes, with only a 0.02% decrease in accuracy compared to a non-ZK execution when testing on the CIFAR-10 dataset. Our system is the first to support ZK proofs about neural-network models with over 100 layers with virtually no loss of accuracy.

Fully Homomorphic Encryption (FHE) schemes enable to compute over encrypted data. Among them, TFHE [CGGI17] has the great advantage of offering an efficient method for bootstrapping noisy ciphertexts, i.e., reduce the noise. Indeed, homomorphic computation increases the noise in ciphertexts and might compromise the encrypted message. TFHE bootstrapping, in addition to reducing the noise, also evaluates (for free) univariate functions expressed as look-up tables. It however requires to have the most significant bit of the plaintext to be known a priori, resulting in the loss of one bit of space to store messages. Furthermore it represents a non negligible overhead in terms of computation in many use cases. In this paper, we propose a solution to overcome this limitation, that we call Programmable Bootstrapping Without Padding (WoP-PBS). This approach relies on two building blocks. The first one is the multiplication à la BFV [FV12] that we incorporate into TFHE. This is possible thanks to a thorough noise analysis showing that correct multiplications can be computed using practical TFHE parameters. The second building block is the generalization of TFHE bootstrapping introduced in this paper. It offers the flexibility to select any chunk of bits in an encrypted plaintext during a bootstrap. It also enables to evaluate many LUTs at the same time when working with small enough precision. All these improvements are particularly helpful in some applications such as the evaluation of Boolean circuits (where a bootstrap is no longer required in each evaluated gate) and, more generally, in the efficient evaluation of arithmetic circuits even with large integers. Those results improve TFHE circuit bootstrapping as well. Moreover, we show that bootstrapping large precision integers is now possible using much smaller parameters than those obtained by scaling TFHE ones.

Consider a server with a large set $S$ of strings $\{x_1,x_2, \dots,x_N\}$ that would like to publish a small hash $h$ of its set $S$ such that any client with a string $y$ can send the server a short message allowing it to learn $y$ if $y \in S$ and nothing otherwise. In this work, we study this problem of two-round private set intersection (PSI) with low (asymptotically optimal) communication cost, or what we call laconic private set intersection ($\ell$PSI) and its extensions. This problem is inspired by the recent general frameworks for laconic cryptography [Cho et al. CRYPTO 2017, Quach et al. FOCS'18]. We start by showing the first feasibility result for realizing $\ell$PSI based on the CDH assumption, or LWE with polynomial noise-to-modulus ratio. However, these feasibility results use expensive non-black-box cryptographic techniques leading to significant inefficiency. Next, with the goal of avoiding these inefficient techniques, we give a construction of $\ell$PSI schemes making only black-box use of cryptographic functions. Our construction is secure against semi-honest receivers, malicious senders and reusable in the sense that the receiver's message can be reused across any number of executions of the protocol. The scheme is secure under the $\phi$-hiding, decisional composite residuosity and subgroup decision assumptions. Finally, we show natural applications of $\ell$PSI to realizing a semantically-secure encryption scheme that supports detection of encrypted messages belonging to a set of ``illegal'' messages (e.g., an illegal video) circulating online. Over the past few years, significant effort has gone into realizing laconic cryptographic protocols. Nonetheless, our work provides the first black-box constructions of such protocols for a natural application setting.

Privacy is a huge concern for cryptocurrencies and blockchains as most of these systems log everything in the clear. This has resulted in several academic and industrial initiatives to address privacy. Starting with the UTXO model of Bitcoin, initial works brought confidentiality and anonymity to payments. Recent works have expanded to support more generalized forms of private computation. Such solutions tend to be highly involved as they rely on advanced cryptographic primitives and creative techniques to handle issues related to dealing with private records (e.g. concurrency and double spending). This situation makes it hard to comprehend the current state-of-the-art, much less build on top of it. To address these challenges, we develop a systematization of knowledge for privacy-preserving solutions in blockchain. To the best of our knowledge, our work is the first of its kind. After motivating design challenges, we devise two systematization frameworks---the first as a stepping stone to the second---and use them to study the state-of-the-art. For our first framework, we study the zero-knowledge proof systems used in surveyed solutions, based on their key features and limitations. Our second is for blockchain privacy-preserving solutions; we define several dimensions to categorize the surveyed schemes and, in doing so, identify two major paradigms employed to achieve private computation. We go on to provide insights to guide solutions' adoption and development. Finally, we touch upon challenges related to limited functionality, practicality, and accommodating new developments.

In this paper, we initiate a study of asymmetric all-or-nothing transforms (or asymmetric AONTs). A (symmetric) $t$-all-or-nothing transform is a bijective mapping defined on the set of $s$-tuples over a specified finite alphabet. It is required that knowledge of all but $t$ outputs leaves any $t$ inputs completely undetermined. There have been numerous papers developing the theory of AONTs as well as presenting various applications of AONTs in cryptography and information security. In this paper, we replace the parameter $t$ by two parameters $t_o$ and $t_i$, where $t_i \leq t_o$. The requirement is that knowledge of all but $t_o$ outputs leaves any $t_i$ inputs completely undetermined. When $t_i < t_o$, we refer to the AONT as asymmetric. We give several constructions and bounds for various classes of asymmetric AONTs, especially those with $t_i = 1$ or $t_i = 2$. We pay particular attention to linear transforms, where the alphabet is a finite field $F_q$ and the mapping is linear.

The recent KEMTLS protocol (Schwabe, Stebila and Wiggers,CCS’20) is a promising design for a quantum-safe TLS handshake protocol. Focused on the web setting, wherein clients learn server public-key certificates only during connection establishment, a drawback of KEMTLS compared to TLS 1.3 is that it introduces an additional round trip before the server can send data, and an extra one for the client as well in the case of mutual authentication. In many scenarios, including IoT and embedded settings, client devices may however have the targeted server certificate pre-loaded, so that such performance penalty seems unnecessarily restrictive. This work proposes a variant of KEMTLS tailored to such scenarios. Our protocol leverages the fact that clients know the server public keys in advance to decrease handshake latency while protecting client identities. It combines medium-lived with long-term server public keys to enable a delayed form of forward secrecy even from the first data flow on, and full forward secrecy upon the first round trip. The new protocol is proved to achieve strong security guarantees, based on the security of the underlying building blocks, in a new model for multi-stage key exchange with medium-lived keys.

In distributed computations and cryptography, it is desirable to record events on a public ledger, such that later alterations are computationally infeasible. An implementation of this idea is called blockchain, which is a distributed protocol that allows the creation of an immutable ledger. While such an idea is very appealing, the ledger may be contaminated with incorrect, illegal, or even dangerous data, and everyone running the blockchain protocol has no option but to store and propagate the unwanted data. The ledger is bloated over time, and it is not possible to remove redundant information. Finally, missing data cannot be inserted later. Redactable blockchains were invented to allow the ledger to be mutated in a controlled manner. To date, redactable blockchains support at most two types of redactions: block modification and removal. The next logical step is to support block insertions. However, we show that this seemingly innocuous enhancement renders all previous constructs insecure. We put forward a model for blockchains supporting all three redaction operations, and construct a blockchain that is provably secure under this formal definition.

Side-channel attacks exploit information from physical implementations of cryptographic systems. Cache attacks have improved at recovering information by combining observations of the victim's cache access and knowledge of the cipher’s structure. Cache attacks have been implemented for most Feistel- and SPN-structured block cipher algorithms, but the security of algorithms for special structures has seen little attention. We perform a Flush+Reload attack on MISTY1, a class of block cipher with a recursive structure. The function is performed before the plaintext input S-box and after the ciphertext output S-box, making it difficult to attack the first and last rounds. However, the key scheduling part of MISTY1 leaks many bits of the key, which, together with the leakage of partial bits of the round key during encryption, is sufficient to recover it. We design an algorithm that can recover the MISTY1 128-bit key after observing encryption one time, and then use leakage during encryption to reduce its complexity. We experiment on 32- and 64-byte cache line environments. An adversary need observe as little as 5 encryptions to recover the 128-bit key in 0.035 second in the first case, and 10 encryptions to recover the key in 2.1 hours in the second case.

Homomorphic encryption (HE) is a useful variant of public key encryption (PKE), but it has a drawback that HE cannot fully achieve IND-CCA2 security, which is a standard security notion for PKE. Beyond existing HE schemes achieving weaker IND-CCA1 security, Emura et al.\ (PKC 2013) proposed the notion of \lq\lq keyed\rq\rq{} version of HE, called KH-PKE, which introduces an evaluation key controlling the functionality of homomorphic operations and achieves security stronger than IND-CCA1 and as close to IND-CCA2 as possible. After Emura et al.'s scheme which can evaluate linear polynomials only, Lai et al.\ (PKC 2016) proposed a fully homomorphic KH-PKE, but it requires indistinguishability obfuscation and hence has a drawback in practical feasibility. In this paper, we propose a \lq\lq two-level\rq\rq{} KH-PKE scheme for evaluating degree-two polynomials, by cleverly combining Emura et al.'s generic framework with a recent efficient two-level HE by Attrapadung et al.\ (ASIACCS 2018). Our scheme is the first KH-PKE that can handle non-linear polynomials while keeping practical efficiency.

For a hyperelliptic curve defined over a finite field $\bbbf_{q^n}$ with $n>1$, the discrete logarithm problem is subject to index calculus attacks. We exploit the endomorphism of the curve to reduce the size of the factorization basis and hence improve the complexity of the index calculus attack for certain families of ordinary elliptic curves and genus 2 hyperelliptic Jacobians defined over finite fields. This approach adds an extra cost when performing operation on the factor basis, but the experiences show that reducing the size of the factor basis allows to have a gain on the total complexity of index calculus algorithm with respect to the generic attacks.

In recent years machine learning has become increasingly mainstream across industries. Additionally, Graphical Processing Unit (GPU) accelerators are widely deployed in various neural network (NN) applications, including image recognition for autonomous vehicles and natural language processing, among others. Since training a powerful network requires expensive data collection and computing power, its design and parameters are often considered a secret intellectual property of their manufacturers. However, hardware accelerators can leak crucial information about the secret neural network designs through side-channels, like Electro-Magnetic (EM) emanations, power consumption, or timing. We propose and evaluate non-invasive and passive reverse engineering methods to recover NN designs deployed on GPUs through EM side-channel analysis. We employ a well-known technique of simple EM analysis and timing analysis of NN layers execution. We consider commonly used NN architectures, namely Multilayer Perceptron and Convolutional Neural Networks. We show how to recover the number of layers and neurons as well as the types of activation functions. Our experimental results are obtained on a setup that is as close as possible to a real-world device in order to properly assess the applicability and extendability of our methods. We analyze the NN execution of a PyTorch python framework implementation running on Nvidia Jetson Nano, a module computer embedding a Tegra X1 SoC that combines an ARM Cortex-A57 CPU and a 128-core GPU within a Maxwell architecture. Our results show the importance of side-channel protections for NN accelerators in real-world applications.

In CRYPTO 2019, Gohr shows that well-trained neural networks can perform cryptanalytic distinguishing tasks superior to traditional differential distinguishers. Moreover, applying an unorthodox key guessing strategy, an 11-round key-recovery attack on a modern block cipher Speck32/64 improves upon the published state-of-the-art result. This calls into the next questions. To what extent is the advantage of machine learning (ML) over traditional methods, and whether the advantage generally exists in the cryptanalysis of modern ciphers? To answer the first question, we devised ML-based key-recovery attacks on more extended round-reduced Speck32/64. We achieved an improved 12-round and the first practical 13-round attacks. The essential for the new results is enhancing a classical component in the ML-based attacks, that is, the neutral bits. To answer the second question, we produced various neural distinguishers on round-reduced Simon32/64 and provided comparisons with their pure differential-based counterparts.

In this work, we propose generic and novel side-channel assisted chosen-ciphertext attacks on NTRU-based key encapsulation mechanisms (KEMs). These KEMs are IND-CCA secure, that is, they are secure in the chosen-ciphertext model. Our attacks involve the construction of malformed ciphertexts. When decapsulated by the target device, these ciphertexts ensure that a targeted intermediate variable becomes very closely related to the secret key. An attacker, who can obtain information about the secret-dependent variable through side-channels, can subsequently recover the full secret key. We propose several novel CCAs which can be carried through by using side-channel leakage from the decapsulation procedure. The attacks instantiate three different types of oracles, namely a plaintext-checking oracle, a decryption-failure oracle, and a full-decryption oracle, and are applicable to two NTRU-based schemes, which are NTRU and NTRU Prime. The two schemes are candidates in the ongoing NIST standardization process for post-quantum cryptography. We perform experimental validation of the attacks on optimized and unprotected implementations of NTRU-based schemes, taken from the open-source pqm4 library, using the EM-based side-channel on the 32-bit ARM Cortex-M4 microcontroller. All of our proposed attacks are capable of recovering the full secret key in only a few thousand chosen ciphertext queries on all parameter sets of NTRU and NTRU Prime. Our attacks, therefore, stress on the need for concrete side-channel protection strategies for NTRU-based KEMs.

Deep learning-based side-channel analysis is an effective way of performing profiling attacks on power and electromagnetic leakages, even against targets protected with countermeasures. While many research papers have reported successful results, they typically focus on profiling and attacking a single device, assuming that leakages are similar between devices of the same type. However, this assumption is not always realistic due to variations in hardware and measurement setups, creating what is known as the portability problem. Profiling multiple devices has been proposed as a solution, but obtaining access to these devices may pose a challenge for attackers. This paper proposes a new approach to overcome the portability problem by introducing a neural network layer assessment methodology based on the ablation paradigm. This methodology evaluates the sensitivity and resilience of each layer, providing valuable knowledge to create a Multiple Device Model from Single Device (MDMSD). Specifically, it involves ablating a specific neural network section and performing recovery training. As a result, the profiling model, trained initially on a single device, can be generalized to leakage traces measured from various devices. By addressing the portability problem through a single device, practical side-channel attacks could be more accessible and effective for attackers.

Searchable Symmetric Encryption (SSE) enables a client to outsource a database to an untrusted server, while retaining the ability to securely search the data. The performance bottleneck of classic SSE schemes typically does not come from their fast, symmetric cryptographic operations, but rather from the cost of memory accesses. To address this issue, many works in the literature have considered the notion of locality, a simple design criterion that helps capture the cost of memory accesses in traditional storage media, such as Hard Disk Drives. A common thread among many SSE schemes aiming to improve locality is that they are built on top of new memory allocation schemes, which form the technical core of the constructions. The starting observation of this work is that for newer storage media such as Solid State Drives (SSDs), which have become increasingly common, locality is not a good predictor of practical performance. Instead, SSD performance mainly depends on page efficiency, that is, reading as few pages as possible. We define this notion, and identify a simple memory allocation problem, Data-Independent Packing (DIP), that captures the main technical challenge required to build page-efficient SSE. As our main result, we build a page-efficient and storage-efficient data-independent packing scheme, and deduce the Tethys SSE scheme, the first SSE scheme to achieve at once O(1) page efficiency and O(1) storage efficiency. The technical core of the result is a new generalization of cuckoo hashing to items of variable size. Practical experiments show that this new approach achieves excellent performance.

We put forth a keyless wallet, a cryptocurrency wallet in which money can be spent using a password alone, and no private keys are required. It requires a smart contract blockchain. We propose two schemes. In the first, the user sets a short wallet password and can spend their money at a prespecified maturity date using the password alone. Using this as a stepping stone, we propose a second scheme, in which the user uses an OTP authenticator seed to generate a long series of time-based OTP passwords for the foreseeable future. These are encrypted and organized in a Merkle tree whose root is stored in a smart contract. The user can spend funds at any time by simply visually providing the current OTP password from an air gapped device. These OTPs can be relatively short: Just $6$ alphanumeric characters suffice. Our OTP scheme can work in proof-of-stake as well as static and variable difficulty proof-of-work blockchains. The low-entropy in the passwords and OTPs in our scheme is protected from brute force attempts by requiring that an adversary accompany any brute force attempt by a transaction on the chain. This quickly incurs enormous economic costs for the adversary. Thus, we develop the first decentralized rate limiting scheme. We use Witness Encryption (WE) to construct a timelock encryption scheme in which passwords are encrypted from past into future blocks by leveraging the NP-language expressing proof-of-work or proof-of-stake performed as the witness. Witness Encryption is a currently impractical cryptographic primitive, but our scheme may become practical as these primitives are further developed.

Abstract—CARiMoL is a novel run-time Configurable Hardware Accelerator for Ring and Module Lattice-based postquantum cryptography. It’s flexible design can be configured to key-pair generation, encapsulation, and decapsulation for NewHope and CRYSTALS-Kyber schemes using same hardware. CARiMoL offers run-time configurability for multiple security levels of NewHope and CRYSTALS-Kyber schemes, supporting both Chosen-Plaintext Attack (CPA) and Chosen-Ciphertext Attack (CCA) secure implementations. To the best of our knowledge, it is the first systematically designed full scale hardware accelerator for CCA-complaint multiple LBC schemes that supports run-time reconfigurability without the use of processor such as ARM Cortex series or soft core such as popular RISC-V processors. CARiMol performs logic sequencing on runtime and eliminates the cycle overhead associated with fetch and decode instructions. For the simultaneous use of Ring-LWE and Module-LWE, CARiMoL’s single hardware accelerator has 7x less area overhead as compared to combined standalone design of these schemes. CARiMoL exploits parallelism and extensive resource sharing among the different LBC schemes to achieve high performance and efficiency. Despite its reconfigurability, CARiMoL offers substantial speedup compared to the state-ofthe- art, i.e., 9x over NewHope-1024, 10x over NewHope-512, 17x over CRYSTALS-Kyber-1024, and 18x over CRYSTALSKyber-512.

Many interesting applications of pattern matching (e.g. deep-packet inspection or medical data analysis) target very sensitive data. In particular, spotting illegal behaviour in internet traffic conflicts with legitimate privacy requirements, which usually forces users (e.g. children, employees) to blindly trust an entity that fully decrypts their traffic in the name of security. The compromise between traffic analysis and privacy can be achieved through searchable encryption. However, as the traffic data is a stream and as the patterns to search are bound to evolve over time (e.g. new virus signatures), these applications require a kind of searchable encryption that provides more flexibility than the classical schemes. We indeed need to be able to search for patterns of variable sizes in an arbitrary long stream that has potentially been encrypted prior to pattern identification. To stress these specificities, we call such a scheme a stream encryption supporting pattern matching. Recent papers use bilinear groups to provide public key constructions supporting these features. These solutions are lighter than more generic ones (e.g. fully homomorphic encryption) while retaining the adequate expressivity to support pattern matching without harming privacy more than needed. However, all existing solutions in this family have weaknesses with respect to efficiency and security that need to be addressed. Regarding efficiency, their public key has a size linear in the size of the alphabet, which can be quite large, in particular for applications that naturally process data as bytestrings. Regarding security, they all rely on a very strong computational assumption that is both interactive and specially tailored for this kind of scheme. In this paper, we tackle these problems by providing two new constructions using bilinear groups to support pattern matching on encrypted streams. Our first construction shares the same strong assumption but dramatically reduces the size of the public key by removing the dependency on the size of the alphabet, while nearly halving the size of the ciphertext. On a typical application with large patterns, our public key is two order of magnitude smaller that the one of previous schemes, which demonstrates the practicality of our approach. Our second construction manages to retain most of the good features of the first one while exclusively relying on a simple (static) variant of DDH, which solves the security problem of previous works.

Differential Fault Analysis (DFA) is a well known cryptanalytic technique that exploits faulty outputs of an encryption device. Despite its popularity and similarity with the classical Differential Analysis (DA), a thorough analysis explaining DFA from a designer's point of view is missing in the literature. To the best of our knowledge, no DFA immune cipher at an algorithmic level has been proposed so far. Furthermore, all known DFA countermeasures somehow depend on the device/protocol or on the implementation such as duplication/comparison. As all of these are outside the scope of the cipher designer, we focus on designing a primitive which can protect from DFA on its own. We present the first concept of cipher level DFA resistance which does not rely on any device/protocol related assumption, nor does it depend on any form of duplication. Our construction is simple, software/hardware friendly and DFA security scales up with the state size. It can be plugged before and/or after (almost) any symmetric key cipher and will ensure a non-trivial search complexity against DFA. One key component in our DFA protection layer is an SBox with linear structures. Such SBoxes have never been used in cipher design as they generally perform poorly against differential attacks. We argue that they in fact represent an interesting trade-off between good cryptographic properties and DFA resistance. As a proof of concept, we construct a DFA protecting layer, named DEFAULT-LAYER, as well as a full-fledged block cipher DEFAULT. Our solutions compare favourably to the state-of-the-art, offering advantages over the sophisticated duplication based solutions like impeccable circuits/CRAFT or infective countermeasures.

Lattice-based schemes are promising candidates to replace the current public-key cryptographic infrastructure in wake of the looming threat of quantum computers. One of the Round 3 candidates of the ongoing NIST post-quantum standardization effort is FrodoKEM. It was designed to provide conservative security, which comes with the caveat that implementations are often bigger and slower compared to alternative schemes. In particular, the most time-consuming arithmetic operation of FrodoKEM is the multiplication of matrices with entries in Z_q. In this work, we investigate the performance of different matrix multiplication approaches in the specific setting of FrodoKEM. We consider both optimized “naïve” matrix multiplication with cubic complexity, as well as the Strassen multiplication algorithm which has a lower asymptotic run-time complexity. Our results show that for the proposed parameter sets of FrodoKEM we can improve over the state-of-the-art implementation with a row-wise blocking and packing approach, denoted as RWCF in the following. For the matrix multiplication in FrodoKEM, this results in a factor two speed-up. The impact of these improvements on the full decapsulation operation is up to 22 percent. We additionally show that for batching use-cases, where many inputs are processed at once, the Strassen approach can be the best choice from batch size 8 upwards. For a practically-relevant batch size of 128 inputs the observed speed-up is in the range of 5 to 11 percent over using the efficient RWCF approach and this speed-up grows with the batch size.

The design of zkSNARKs is increasingly complicated and requires familiarity with a broad class of cryptographic and algebraic tools. This complexity in zkSNARK design also increases the difficulty in zkSNARK implementation, analysis, and optimization. To address this complexity, we develop a new workflow for designing and implementing zkSNARKs, called $\mathsf{VOProof}$. In $\mathsf{VOProof}$, the designer only needs to construct a \emph{Vector Oracle (VO) protocol} that is intuitive and straightforward to design, and then feeds this protocol to our \emph{VO compiler} to transform it into a fully functional zkSNARK. This new workflow conceals most algebraic and cryptographic operations inside the compiler, so that the designer is no longer required to understand these cumbersome and error prone procedures. Moreover, our compiler can be fine-tuned to compile one VO protocol into multiple zkSNARKs with different tradeoffs. We apply $\mathsf{VOProof}$ to construct three general-purpose zkSNARKs targeting three popular representations of arithmetic circuits: the Rank-1 Constraint System (R1CS), the Hadamard Product Relation (HPR), and the $\mathsf{PLONK}$ circuit. These zkSNARKs have shorter and more intuitive descriptions, thus are easier to implement and optimize compared to prior works. To evaluate their performance, we implement a Python framework for describing VO protocols and compiling them into working Rust code of zkSNARKs. Our evaluation shows that the $\mathsf{VOProof}$-based zkSNARKs have competitive performance, especially in proof size and verification time, e.g., both reduced by roughly $50\%$ compared to $\mathsf{Marlin}$ (Chiesa et al., EUROCRYPT 2020). These improvements make the $\mathsf{VOProof}$-based zkSNARKs more preferable in blockchain scenarios where the proof size and verification time are critical.

We give an attribute-based encryption system for Turing Machines that is provably secure assuming only the existence of identity-based encryption (IBE) for large identity spaces. Currently, IBE is known to be realizable from most mainstream number theoretic assumptions that imply public key cryptography including factoring, the search Diffie-Hellman assumption, and the Learning with Errors assumption. Our core construction provides security against an attacker that makes a single key query for a machine $T$ before declaring a challenge string $w^*$ that is associated with the challenge ciphertext. We build our construction by leveraging a Garbled RAM construction of Gentry, Halevi, Raykova, and Wichs; however, to prove security we need to introduce a new notion of security called iterated simulation security. We then show how to transform our core construction into one that is secure for an a-priori bounded number $q = q(\lambda)$ of key queries that can occur either before or after the challenge ciphertext. We do this by first showing how one can use a special type of non-committing encryption to transform a system that is secure only if a single key is chosen before the challenge ciphertext is declared into one where the single key can be requested either before or after the challenge ciphertext. We give a simple construction of this non-committing encryption from public key encryption in the Random Oracle Model. Next, one can apply standard combinatorial techniques to lift from single-key adaptive security to $q$-key adaptive security.

A core goal of the NIST PQC competition is to produce public-key encryption (PKE) schemes which, even if attacked with a large-scale quantum computer, maintain the security guarantees needed by applications. The main security focus in the NIST PQC context has been IND-CCA security, but other applications demand that PKE schemes provide 'anonymity' (Bellare et al., ASIACRYPT 2001), and 'robustness' (Abdalla et al., TCC 2010). Examples of such applications include anonymous communication systems, cryptocurrencies, anonymous credentials, searchable encryption, and auction protocols. Almost nothing is known about how to build post-quantum PKE schemes offering these security properties. In particular, the status of the NIST PQC candidates with respect to anonymity and robustness is unknown. This paper initiates a systematic study of anonymity and robustness for post-quantum PKE schemes. Firstly, we identify implicit rejection as a crucial design choice shared by most post-quantum KEMs, show that implicit rejection renders prior results on anonymity and robustness for KEM-DEM PKEs inapplicable, and transfer prior results to the implicit-rejection setting where possible. Secondly, since they are widely used to build post-quantum PKEs, we examine how the Fujisaki-Okamoto (FO) transforms (Fujisaki and Okamoto, Journal of Cryptology 2013) confer robustness and enhance weak anonymity of a base PKE. We then leverage our theoretical results to study the anonymity and robustness of three NIST KEM finalists---Saber, Kyber, and Classic McEliece---and one alternate, FrodoKEM. Overall, our findings for robustness are definitive: we provide positive robustness results for Saber, Kyber, and FrodoKEM, and a negative result for Classic McEliece. Our negative result stems from a striking property of KEM-DEM PKE schemes built with the Classic McEliece KEM: for any message 'm', we can construct a single hybrid ciphertext 'c' which decrypts to the chosen 'm' under any Classic McEliece private key. Our findings for anonymity are more mixed: we identify barriers to proving anonymity for Saber, Kyber, and Classic McEliece. We also found that in the case of Saber and Kyber, these barriers lead to issues with their IND-CCA security claims. We have worked with the Saber and Kyber teams to fix these issues, but they remain unresolved. On the positive side, we were able to prove anonymity for FrodoKEM and a variant of Saber introduced by D'Anvers et al. (AFRICACRYPT 2018). Our analyses of these two schemes also identified technical gaps in their IND-CCA security claims, but we were able to fix them.

The Tower variant of the Number Field Sieve (TNFS) is known to be asymptotically the most efficient algorithm to solve the discrete logarithm problem in finite fields of medium characteristics, when the extension degree is composite. A major obstacle to an efficient implementation of TNFS is the collection of algebraic relations, as it happens in dimension greater than 2. This requires the construction of new sieving algorithms which remain efficient as the dimension grows. In this article, we overcome this difficulty by considering a lattice enumeration algorithm which we adapt to this specific context. We also consider a new sieving area, a high-dimensional sphere, whereas previous sieving algorithms for the classical NFS considered an orthotope. Our new sieving technique leads to a much smaller running time, despite the larger dimension of the search space, and even when considering a larger target, as demonstrated by a record computation we performed in a 521-bit finite field GF(p^6). The target finite field is of the same form than finite fields used in recent zero-knowledge proofs in some blockchains. This is the first reported implementation of TNFS.

We cryptanalyse the SIDH-based oblivious pseudorandom function from supersingular isogenies proposed at Asiacrypt'20 by Boneh, Kogan and Woo. To this end, we give an attack on an assumption, the auxiliary one-more assumption, that was introduced by Boneh et al. and we show that this leads to an attack on the oblivious PRF itself. The attack breaks the pseudorandomness as it allows adversaries to evaluate the OPRF without further interactions with the server after some initial OPRF evaluations and some offline computations. More specifically, we first propose a polynomial-time attack. Then, we argue it is easy to change the OPRF protocol to include some countermeasures, and present a second subexponential attack that succeeds in the presence of said countermeasures. Both attacks break the security parameters suggested by Boneh et al. Furthermore, we provide a proof of concept implementation as well as some timings of our attack. Finally, we examine the generation of one of the OPRF parameters and argue that a trusted third party is needed to guarantee provable security.