In this work, we investigate the BGV scheme as implemented in HElib. We begin by performing an implementation-specific noise analysis of BGV. This allows us to derive much tighter bounds than what was previously done. To confirm this, we compare our bounds against the state of the art. We find that, while our bounds are at most $1.8$ bits off the experimentally observed values, they are as much as $29$ bits tighter than previous work. Finally, to illustrate the importance of our results, we propose new and optimised parameters for HElib. In HElib, the special modulus is chosen to be $k$ times larger than the current ciphertext modulus $Q_i$. For a ratio of subsequent ciphertext moduli $\log\left( \frac{Q_i}{Qi−1}\right) = 54$ (a very common choice in HElib), we can optimise $k$ by up to $26$ bits. This means that we can either enable more multiplications without having to switch to larger parameters, or reduce the size of the evaluation keys, thus reducing on communication costs in relevant applications. We argue that our results are near-optimal.

Thesecurityofmanyprotocolssuchasvotingandblockchains relies on a secure source of randomness. Decentralised Randomness Beacon (DRB) has been considered as a promising approach, where a set of participants jointly generates a sequence of random outputs. While the DRBs have been extensively studied, they failed to capture the advantage that some participants learn random outputs earlier than other participants. In time-sensitive protocols whose execution depends on the randomness from a DRB, such an advantage allows the adversary to behave adaptively according to random outputs, compromising the fairness and/or security in these protocols. In this paper, we formalise a new property, delivery-fairness, to quantify the advantage. In particular, we distinguish two aspects of delivery-fairness, namely length-advantage, i.e., how many random outputs an adversary can learn earlier than correct participants, and time-advantage, i.e., how much time an adversary can learn a given random output earlier than correct participants. In addition, we prove the lower bound of delivery-fairness showing optimal guarantee. We further analyse the delivery-fairness guarantee of state-of-the-art DRBs and discuss insights, which, we show through case studies, could help improve delivery-fairness of existing systems to its optimal.

In this paper, we present the first chosen-ciphertext (CC) cache-timing attacks on the reference implementation of HQC. We build a cache-timing based distinguisher for implementing a plaintext-checking (PC) oracle. The PC oracle uses side-channel information to check if a given ciphertext decrypts to a given message. This is done by identifying a vulnerability during the generating process of two vectors in the reference implementation of HQC. We also propose a new method of using PC oracles for chosen-ciphertext side-channel attacks against HQC, which may have independent interest. We show a general proof-of-concept attack, where we use the Flush&Reload technique and also derive, in more detail, a practical attack on an HQC execution on Intel SGX, where the Prime&Probe technique is used. We show the exact path to do key recovery by explaining the detailed steps, using the PC oracle. In both scenarios, the new attack requires $53,857$ traces on average with much fewer PC oracle calls than the timing attack of Guo et al. CHES 2022 on an HQC implementation.

This paper combines techniques from several previous papers with some modifications to improve the previous cryptanalysis of 3-round Keccak-256. Furthermore, we propose a fast rebuilding method to improve the efficiency of solving equation systems. As a result, the guessing times of finding a preimage for 3-round Keccak-256 are decreased from $2^{65}$ to $2^{52}$, and the solving time of each guess is decreased from $2^{9}$ 3-round Keccak calls to $2^{5.3}$ 3-round Keccak calls. We identify a preimage of all '0' digest for 3-round Keccak-256 to support the effectiveness of our methodology.

Secure neural network inference has been a promising solution to private Deep-Learning-as-a-Service, which enables the service provider and user to execute neural network inference without revealing their private inputs. However, the expensive overhead of current schemes is still an obstacle when applied in real applications. In this work, we present \textsc{Meteor}, an online communication-efficient and fast secure 3-party computation neural network inference system aginst semi-honest adversary in honest-majority. The main contributions of \textsc{Meteor} are two-fold: \romannumeral1) We propose a new and improved 3-party secret sharing scheme stemming from the \textit{linearity} of replicated secret sharing, and design efficient protocols for the basic cryptographic primitives, including linear operations, multiplication, most significant bit extraction, and multiplexer. \romannumeral2) Furthermore, we build efficient and secure blocks for the widely used neural network operators such as Matrix Multiplication, ReLU, and Maxpool, along with exploiting several specific optimizations for better efficiency. Our total communication with the setup phase is a little larger than SecureNN (PoPETs'19) and \textsc{Falcon} (PoPETs'21), two state-of-the-art solutions, but the gap is not significant when the online phase must be optimized as a priority. Using \textsc{Meteor}, we perform extensive evaluations on various neural networks. Compared to SecureNN and \textsc{Falcon}, we reduce the online communication costs by up to $25.6\times$ and $1.5\times$, and improve the running-time by at most $9.8\times$ (resp. $8.1\times$) and $1.5\times$ (resp. $2.1\times$) in LAN (resp. WAN) for the online inference.

Multiparty garbling is the most popular approach for constant-round secure multiparty computation (MPC). Despite being the focus of significant research effort, instantiating prior approaches to multiparty garbling results in constant-round MPC that can not realistically accommodate large numbers of parties. In this work we present the first global-scale multiparty garbling protocol. The per-party communication complexity of our protocol decreases as the number of parties participating in the protocol increases---for the first time matching the asymptotic communication complexity of non-constant round MPC protocols. Our protocol achieves malicious security in the honest-majority setting and relies on the hardness of the Learning Party with Noise assumption.

In LWE-based KEMs, observed decryption errors leak information about the secret key in the form of equations or inequalities. Several practical fault attacks have already exploited such leakage by either directly applying a fault or enabling a chosen-ciphertext attack using a fault. When the leaked information is in the form of inequalities, the recovery of the secret key is not trivial. Recent methods use either statistical or algebraic methods (but not both), with some being able to handle incorrect information. We answer this question positively by proposing an error-tolerant combination of statistical and algebraic methods that make use of the advantages of both approaches. The combination enables us to improve upon existing methods -- we use both fewer inequalities and are more resistant to errors. We further provide precise security estimates based on the number of available inequalities. Our recovery method applies to several types of implementation attacks in which decryption errors are used in a chosen-ciphertext attack. We practically demonstrate the improved performance of our approach in a key-recovery attack against Kyber with fault-induced decryption errors.

Non-interactive zero-knowledge proofs (NIZKs) and in particular succinct NIZK arguments of knowledge (so called zk-SNARKs) increasingly see real-world adoption in large and complex systems. A requirement that turns out to be important for NIZKs is ensuring non-malleability of proofs, which can be achieved via the property of simulation extractability (SE). Moreover, many zk-SNARKs require a trusted setup, i.e., a common reference string (CRS), and in practice it is desirable to reduce the trust in the CRS generation. Latter can be achieved via the notions of subversion or updatable CRS. Another important property when deployed in large and complex systems is the secure composition of protocols, e.g., via using the Universal Composability (UC) framework. Relying on the UC frameworks allows to arbitrarily and securely compose protocols in a modular way. In this work, we are interested in whether zk-SNARKs can provide all these desired properties. This is a tricky task as the UC framework rules out several natural techniques for such a construction. Our main result is to show that achieving these properties is indeed possible in a generic and modular way when slightly relaxing the succinctness properties of zk-SNARKs to those of a circuit-succinct NIZK which is not witness-succinct, i.e., by increasing the proof size of the underlying zk-SNARK by the size of the witness $w$. We will argue that for various practical applications of zk-SNARKs this overhead is perfectly tolerable. Our starting point is a framework by Abdolmaleki et al. called Lamassu (ACM CCS'20) which we extend in several directions. Moreover, we implement our compiler on top of Sonic (ACM CCS'19) and provide benchmarks as well as a discussion on the choice of the required primitives.

While the efficiency of secure multi-party computation protocols has greatly increased in the last few years, these improvements and protocols are often based on rather unrealistic, idealised, assumptions about how technology is deployed in the real world. In this work we examine multi-party computation protocols in the presence of two major constraints present in deployed systems. Firstly, we consider the situation where the parties are connected not by direct point-to-point connections, but by a star-like topology with a few central post-office style relays. Secondly, we consider MPC protocols with a strong honest majority ($n \gg t/2$) in which we have stragglers (some parties are progressing slower than others). We model stragglers by allowing the adversary to delay messages to and from some parties for a given length of time. We first show that having only a single honest rely is enough to ensure consensus of the messages sent within a protocol; secondly, we show that special care must be taken to describe multiplication protocols in the case of relays and stragglers and that some well known protocols do not guarantee privacy and correctness in this setting; thirdly, we present an efficient honest-majority MPC protocol which can be run on top of the relays and which provides active-security with abort in the case of a strong honest majority, even when run with stragglers. We back up our protocol presentation with both experimental evaluations and simulations of the effect of the relays and delays on our protocol.

The TLS (Transport Layer Security) protocol is the most important, most attacked, most analysed and most used cryptographic protocol in the world today. TLS is critical to the integrity of the Internet, and if it were to be broken e-commerce would become impossible, with very serious implications for the global economy. Furthermore TLS is likely to assume even greater significance in the near future with the rapid growth of an Internet of Things (IoT) -- a multiplicity of internet connected devices all engaged in secure inter-communication. However the impending invention of a Cryptographically Relevant Quantum Computer (CRQC) would represent an existential threat to TLS in its current form. As it stands the latest version TLS1.3, benefiting as it does from years of research and study, provides effective security, but it must soon be updated to resist this new threat. In this research we first undertake a new clean-room implementation of a small-footprint open source TLS1.3, written in C++ and Rust, and suitable for IoT applications. Our implementation is designed to be cryptographically agile, so that it can easily accomodate new post-quantum cryptographic primitives. Next we use this new implementation as a vehicle to study the impact of going post-quantum, with a particular emphasis on the impact on the Internet of Things. Finally we showcase the flexibility of our implementation by proposing an implementation of TLS that uses identity-based encryption to mitigate this impact.

TLS termination, which is essential to network and security infrastructure providers, is an extremely latency sensitive operation that benefits from access to sensitive key material close to the edge. However, increasing regulatory concerns prompt customers to demand sophisticated controls on where their keys may be accessed. While traditional access-control solutions rely on a highly available centralized process to enforce access, the round-trip latency and decreased fault tolerance make this approach unappealing. Furthermore, the desired level of customer control is at odds with customizing the distribution process for each key. To solve this dilemma, we have designed and implemented Portunus, a cryptographic storage and access control system built using a variant of public-key cryptography called attribute-based encryption (ABE). Using Portunus, TLS keys are protected using ABE under a policy chosen by the customer. Each server is issued unique ABE keys based on its attributes, allowing it to decrypt only the TLS keys for which it satisfies the policy. Thus, the encrypted keys can be stored at the edge, with access control enforced passively through ABE. If a server receives a TLS connection but is not authorized to decrypt the necessary TLS key, the request is forwarded directly to the nearest authorized server, further avoiding the need for a centralized coordinator. In comparison, a trivial instantiation of this system using standard public-key cryptography might wrap each TLS key with the key of every authorized data center. This strategy, however, multiplies the storage overhead by the number of data centers. We have deployed Portunus on Cloudflare's global network of over 400 data centers. Our measurements indicate that we can handle millions of requests per second globally, making it one of the largest deployments of ABE.

The usage of convolutional neural networks (CNNs) to break cryptographic systems through hardware side-channels has enabled fast and adaptable attacks on devices like smart cards and TPMs. Current literature proposes fixed CNN architectures designed by domain experts to break such systems, which is time-consuming and unsuitable for attacking a new system. Recently, an approach using neural architecture search (NAS), which is able to acquire a suitable architecture automatically, has been explored. These works use the secret key information in the attack dataset for optimization and only explore two different search strategies using one-dimensional CNNs. We propose a NAS approach that relies only on using the profiling dataset for optimization, making it fully black-box. Using a large-scale experimental parameter study, we explore which choices for NAS, such as 1-D or 2-D CNNs and search strategy, produce the best results on 10 state-of-the-art datasets for Hamming weight and identity leakage models. We show that applying the random search strategy on 1-D inputs results in a high success rate and retrieves the correct secret key using a single attack trace on two of the datasets. This combination matches the attack efficiency of fixed CNN architectures, outperforming them in 4 out of 10 datasets. Our experiments also point toward the need for repeated attack evaluations of machine learning-based solutions in order to avoid biased performance estimates.

Evaluating exact computational resources necessary for factoring large integers by Shor algorithm using an ideal quantum computer is difficult because simplified circuits were used in past experiments, in which qubits and gates were reduced as much as possible by using the features of the integers, though 15 and 21 were factored on quantum computers. In this paper, we implement Shor algorithm for general composite numbers, and factored 96 RSA-type composite numbers up to 9-bit using a quantum computer simulator. In the largest case, $N=511$ was factored within 2 hours. Then, based on these experiments, we estimate the number of gates and the depth of Shor's quantum circuits for factoring 1024-bit and 2048-bit integers. In our estimation, Shor's quantum circuit for factoring 1024-bit integers requires $2.78 \times 10^{11}$ gates, and with depth $2.24 \times 10^{11}$, while $2.23 \times 10^{12}$ gates, and with depth $1.80 \times 10^{12}$ for 2048-bit integers.

We study satisfiability modulo the theory of finite fields and give a decision procedure for this theory. We implement our procedure for prime fields inside the cvc5 SMT solver. Using this theory, we construct SMT queries that verify the correctness of various zero knowledge proof compilers on various input programs. Our experiments show that our implementation is vastly superior to previous approaches (which encode field arithmetic using integers or bit-vectors).

Because of the rapid growth of Internet of Things (IoT), embedded systems have become an interesting target for experienced attackers. ESP32~\cite{tech-ref-man} is a low-cost and low-power system on chip (SoC) series created by Espressif Systems. The firmware extraction of such embedded systems is a real threat to the manufacturer as it breaks its intellectual property and raises the risk of creating equivalent systems with less effort and resources. In 2019, LimitedResults~\cite{LimitedResultsPown} published power glitch attacks which resulted in dumping secure boot and flash encryption keys stored in the eFuses of ESP32. Therefore, Espressif patched this vulnerability and then advised its customers to use ESP32-V3, which is an updated SoC revision. This new version is hardened against fault injection attacks in hardware and software as announced by Espressif~\cite{ESPpatch}. In this paper, we present for the first time a deep hardware security evaluation for ESP32-V3. The main goal of this evaluation is to extract the firmware encryption key stored in the eFuses. This evaluation includes Fault Injection (FI) and Side-Channel (SC) attacks. First, we use Electromagnetic FI (EMFI) in order to show that ESP32-V3 doesn't resist EMFI. However, by experimental results, we show that this version contains a revised bootloader compared to ESP32-V1, which hardens dumping the eFuse keys by FI. Second, we perform a full SC analysis on the AES accelerator of ESP32-V3. We show that an attacker with a physical access to the device can extract all the keys of the hardware AES-256 after collecting 60K power measurements during the execution of the AES block. Third, we present another SC analysis for the firmware decryption mechanism, by targeting the decryption operation during the power up. Using this knowledge, we demonstrate that the full 256-bit AES firmware encryption key, which is stored in the eFuses, can be recovered by SC analysis using 300K power measurements. Finally, we apply practically the firmware encryption attack on Jade hardware wallet \cite{jade}.

Recent years have witnessed a push to bring multi-party computation (MPC) to practice and make it accessible to the end user/programmer. Despite novel ideas, on frontend language design (e.g., Wysteria, Viaduct), backend protocol design and implementation (e.g., ABY, MOTION), or both (e.g., SPDZ), classical compiler optimizations remain largely under-utilized (if not completely unused) in MPC programming. A likely reason is that such optimizations are often applied on a middle-end intermediate representation such as SSA. We put forth a methodology for an MPC programming compilation toolchain, which by mimicking the compilation methodology of standard imperative languages enables middle-end optimizations on MPC, yielding significant improvements. To this direction we devise an MPC circuit compiler that allows MPC programming in what is essentially Python, and inherits the structure (and therefore optimization opportunities) of the classical compilation pipeline. Our key conceptual contribution is advancing an intermediate language, which we call MPC-IR, that can be viewed as the analogue, in an MPC program’s compilation, of (enriched) SSA form. MPC-IR is a particularly appealing intermediate language as it allows backend-independent optimizations, a close analogy to machine independent optimizations in classical compilers. Demonstrating the power of our approach, we focus on a specific backend-independent optimization, SIMD-vectorization: We devise a novel classical-compiler-inspired automatic SIMD-vectorization on MPC-IR, which we show leads to significant speedup in circuit generation time and running time, as well as significant reduction in communication size and number of gates over the corresponding iterative schedule. We implement and benchmark our compiler from a Python-like program to an optimized circuit that can be fed into an MPC backend (for our benchmarks we make use of the MOTION backend for MPC). We view our exhaustive benchmarks as both a way to validate our optimization and end-to-end compiler, and as a contribution, by itself, to a more complete benchmarks suite for MPC programming—such benchmarks suites are common in classical compilers.

We initiate a formal study of individual cryptography Informally speaking, an algorithm Alg is individual if in every implementation of Alg there always exists an individual user that has full knowledge of the cryptographic secrets S used by Alg. In particular, it should be infeasible to design implementations of this algorithm that would hide the secret S by distributing it between a group of parties using an MPC protocol, or via outsourcing it to a trusted execution environment.

This paper describes a formalization of the specification and the algorithm of the public key encryption scheme CRYSTALS-KYBER as well as the verification of its $\delta$-correctness and indistinguishability under chosen plaintext attack (IND-CPA) security proof. The algorithms and proofs were formalized with only minimal assumptions in a modular way to verify the proofs for all possible parameter sets. During the formalization in this flexible setting, problems in the correctness proof were uncovered. Furthermore, the security of CRYSTALS-KYBER under IND-CPA was verified using a game-based approach. As the security property does not hold for the original version of CRYSTALS-KYBER, we only show the IND-CPA security for the latest versions. The security proof was verified under the hardness assumption of the module Learning-with-Errors Problem. The formalization was realized in the theorem prover Isabelle and is foundational.

As the number of blockchain projects grows, efficient cross-chain interoperability becomes more necessary. A common cross-chain protocol is the two-way peg, which is typically used to transfer assets between blockchains and their sidechains. The criticality of cross-chain protocols require that they are designed with strong security models, which can reduce usability in the form of long transfer times. In this paper, we present Flyover, a repayment protocol to speed up the transfer of bitcoins over federated pegs by allowing untrusted liquidity providers to advance funds for the users. Transfer times are reduced because liquidity providers do not have the same security requirements as the underlying cross-chain protocol. We illustrate the Flyover protocol on the cross-chain interoperability protocol that connects Bitcoin to the RSK sidechain and show how Flyover can reduce transfer times without reducing security. In addition to this, Flyover extends the cross-chain protocol by allowing liquidity providers to make smart contract calls on RSK on behalf of the user.

The ChaCha20-Poly1305 AEAD scheme is being increasingly widely deployed in practice. Practitioners need proven security bounds in order to set data limits and rekeying intervals for the scheme. But the formal security analysis of ChaCha20-Poly1305 currently lags behind that of AES-GCM. The only extant analysis (Procter, 2014) contains a flaw and is only for the single-user setting. We rectify this situation. We prove a multi-user security bound on the AEAD security of ChaCha20-Poly1305 and establish the tightness of each term in our bound through matching attacks. We show how our bound differs both qualitatively and quantitatively from the known bounds for AES-GCM, highlighting how subtle design choices lead to distinctive security properties. We translate our bound to the nonce-randomized setting employed in TLS 1.3 and elsewhere, and we additionally improve the corresponding security bounds for GCM. Finally, we provide a simple yet stronger variant of ChaCha20-Poly1305 that addresses the deficiencies highlighted by our analysis.

We propose a single-tiered hybrid Proof-of-Work consensus protocol to encourage decentralization in bitcoin. Our new mechanism comprises coupled puzzles of which properties differ from each other; the one is the extant outsourceable bitcoin puzzle while the other is non-outsourceable. Our new protocol enables miners to solve either puzzle as they want; therefore, blocks can be generated by either puzzle. Our hybrid consensus can be successfully implemented in bitcoin, because it is backward-compatible with existing bitcoin mining equipment(more precisely, existing bitcoin mining ASICs)

Oblivious RAM (ORAM), introduced by Goldreich and Ostrovsky (J. ACM '96), is a primitive that allows a client to perform RAM computations on an external database without revealing any information through the access pattern. For a database of size $N$, well-known lower bounds show that a multiplicative overhead of $\Omega(\log N)$ in the number of RAM queries is necessary assuming $O(1)$ client storage. A long sequence of works culminated in the asymptotically optimal construction of Asharov, Komargodski, Lin, and Shi (CRYPTO '21) with $O(\log N)$ worst-case overhead and $O(1)$ client storage. However, this optimal ORAM construction is known to be secure only in the honest-but-curious setting, where an adversary is allowed to observe the access patterns but not modify the contents of the database. In the malicious setting, where an adversary is additionally allowed to tamper with the database, this construction and many others in fact become insecure. In this work, we construct the first maliciously secure ORAM protocol with worst-case $O(\log N)$ overhead and $O(1)$ client storage assuming one-way functions, which are also necessary. By the $\Omega(\log N)$ ORAM lower bound, our construction is asymptotically optimal. We can also interpret our construction as an online memory checker that matches the bandwidth of the best known online memory checkers while additionally hiding the access pattern. To achieve this, we intricately interleave the ORAM construction of Asharov et al. with online and offline memory checking techniques.

Flow is a high-throughput blockchain with a dedicated step for executing the transactions in a block and a subsequent verification step performed by Verification Nodes. To enforce integrity of the blockchain, the protocol requires a component that prevents Verification Nodes from approving execution results without checking. In our preceding work, we have sketched out an approach called Specialized Proof of Confidential Knowledge (SPoCK). Using SPoCK, nodes can provide evidence to a third party that they both executed the same transaction sequence without revealing the resulting execution trace. The previous Flow white paper presented a basic implementation of such scheme. In this note, we introduce a new SPoCK implementation that is more concise and more efficient than the previous proposal. We first provide a formal generic description of a SPoCK scheme as well as its security definition. Then we propose a new construction of SPoCK based on the BLS signature scheme. We support the new scheme with its proof of security under the appropriate computation assumptions.

Encryption alone is not enough for secure end-to-end encrypted messaging: a server must also honestly serve public keys to users. Key transparency has been presented as an efficient solution for detecting (and hence deterring) a server that attempts to dishonestly serve keys. Key transparency involves two major components: (1) a username to public key mapping, stored and cryptographically committed to by the server, and, (2) an out-of-band consistency protocol for serving short commitments to users. In the setting of real-world deployments and supporting production scale, new challenges must be considered for both of these components. We enumerate these challenges and provide solutions to address them. In particular, we design and implement a memory-optimized and privacy-preserving verifiable data structure for committing to the username to public key store. To make this implementation viable for production, we also integrate support for persistent and distributed storage. We also propose a future-facing solution, termed ''compaction'', as a mechanism for mitigating practical issues that arise from dealing with infinitely growing server data structures. Finally, we implement a consensusless solution that achieves the minimum requirements for a service that consistently distributes commitments for a transparency application, providing a much more efficient protocol for distributing small and consistent commitments to users. This culminates in our production-grade implementation of a key transparency system (Parakeet) which we have open-sourced, along with a demonstration of feasibility through our benchmarks.

The private heavy-hitters problem is a data-collection task where many clients possess private bit strings, and data-collection servers aim to identify the most popular strings without learning anything about the clients' inputs. The recent work of Poplar constructed a protocol for private heavy hitters but their solution was susceptible to additive attacks by a malicious server, compromising both the correctness and the security of the protocol. In this paper, we introduce PLASMA, a private analytics framework that addresses these challenges by using three data-collection servers and a novel primitive, called verifiable incremental distributed point function (VIDPF). PLASMA allows each client to non-interactively send a message to the servers as its input and then go offline. Our new VIDPF primitive employs lightweight techniques based on efficient hashing and allows the servers to non-interactively validate client inputs and preemptively reject malformed ones. PLASMA drastically reduces the communication overhead incurred by the servers using our novel batched consistency checks. Specifically, our server-to-server communication depends only on the number of malicious clients, as opposed to the total number of clients, yielding a $182\times$ and $235\times$ improvement over Poplar and other state-of-the-art sorting-based protocols respectively. Compared to recent works, PLASMA enables both client input validation and succinct communication, while ensuring full security. At runtime, PLASMA computes the 1000 most popular strings among a set of 1 million client-held 32-bit strings in 67 seconds and 256-bit strings in less than 20 minutes respectively.

The increasing popularity of blockchain technology has affected the way we view many fields related to computer science, with E-commerce being no exception. The distributed nature and transparency of blockchain-based systems is one of its main perks, but it also raises some issues when it comes to privacy. Zero-knowledge proofs are very powerful building blocks when it comes to building privacy-preserving protocols, so, naturally, they have attracted a lot of attention in the last years. Following the recent collapse of the very popular crypto exchange FTX, we believe it is important to analyse how such events can be prevented in the future. This paper aims to highlight solutions that use zero-knowledge to prove solvency.

Blockchain is a newly emerging technology, however, it has proven effective in many applications because it provides multiple advantages, mainly as it represents a trust system in which data is encrypted in a way that cannot be tampered with or forged. Because it contains many details such as smart contracts, consensus, authentication, etc. the blockchain is a fertile ground for researchers where they can continually improve previous versions of these concepts. This paper introduces a new multi-signature scheme based on RSA. This scheme is designed to reduce the blockchain's size and prevent known attacks and is also applicable in many other settings that require multi-signatures. Our scheme is in the plain public key model, which means nodes do not need to prove knowledge or possession of their private key. In which, whatever the number of signers, the final signature size is equal to $O(k)$ where $k$ is a security parameter and no interaction between signers is needed. To verify that a number of parties have signed a shared message $m$, a verifier needs the signature, list of signers, and the message $m$. The presented practical short accountable-subgroup multi-signature (ASM) scheme allows a valid signature to disclose which subset generated the signature. It is worth noting that our multi-signatures with public key aggregation is an interactive two-round protocol and a multi-signature model applied to the entire block and not to individual transactions.

We give a construction of a 2-round blind signature scheme based on the hardness of standard lattice problems (Ring/Module-SIS/LWE and NTRU) with a signature size of 22 KB. The protocol is round-optimal and has a transcript size that can be as small as 60 KB. This blind signature is around $4$ times shorter than the most compact lattice-based scheme based on standard assumptions of del Pino and Katsumata (Crypto 2022) and around $2$ times shorter than the scheme of Agrawal et al. (CCS 2022) based on their newly-proposed one-more-SIS assumption. We also give a construction of a ``keyed-verification'' blind signature scheme in which the verifier and the signer need to share a secret key. The signature size in this case is only $48$ bytes, but more work needs to be done to explore the efficiency of the protocol which generates the signature.

Masking has become one of the most effective approaches for securing hardware designs against side-channel attacks. Irrespective of the effort put into correctly implementing masking schemes on a field programmable gate array (FPGA), leakage can be unexpectedly observed. This is due to the fact that the assumption underlying all masked designs, i.e., the leakages of different shares are independent of each other, may no longer hold in practice. In this regard, extreme temperatures have been shown to be an important factor in inducing leakage, even in correctly-masked designs. This has previously been verified using an external heat generator (i.e., a climate chamber). In this paper, we examine whether the leakage can be induced using the circuit components themselves. Specifically, we target masked neural networks (NNs) in FPGAs, with one of the main building blocks being block random access memory (BRAM) and flip-flops (FFs). In this respect, thanks to the inherent characteristics of NNs, our novel internal heat generators leverage solely the memories devoted to storing the user’s input, especially when frequently writing alternating patterns into BRAMs and FFs. The possibility of observing first-order leakage is evaluated by considering one of the most recent and successful first-order secure masked NNs, namely ModuloNET. ModuloNET is specifically designed for FPGAs, where BRAMs are used for storing the inputs and intermediate computations. Our experimental results demonstrate that undesirable first-order leakage can be observed by increasing the temperature when an alternating input is applied to the masked NN. To give a better understanding of the impact of extreme heat, we further perform a similar test on the design with FFs storing the input, where the same conclusion can be drawn.

The threat of chip-level tampering and its detection is a widely researched field. Hardware Trojan insertions are prominent examples of such tamper events. Altering the placement and routing of a design or removing a part of a circuit for side-channel leakage/fault sensitivity amplification are other instances of such attacks. While semi- and fully-invasive physical verification methods can confidently detect such stealthy tamper events, they are costly, time-consuming, and destructive. On the other hand, virtually all proposed non-invasive side-channel methods suffer from noise and, therefore, have low confidence. Moreover, they require activating the tampered part of the circuit (e.g., the Trojan trigger) to compare and detect the modification. In this work, we introduce a general non-invasive post-silicon tamper detection technique applicable to all sorts of tamper events at the chip level without requiring the activation of the malicious circuit. Our method relies on the fact that all classes of physical modifications (regardless of their physical, activation, or action characteristics) alter the impedance of the chip. Hence, characterizing the impedance can lead to the detection of the tamper events. To sense the changes in the impedance, we deploy known RF tools, namely, scattering parameters, in which we inject sine wave signals with high frequencies to the power distribution network (PDN) of the system and measure the “echo” of the signal. The reflected signals in various frequency bands reveal different tamper events based on their impact size on the die. To validate our claims, we performed extensive measurements on several proof-of-concept tampered hardware implementations realized on an FPGA manufactured with a 28 nm technology. Based on these groundbreaking results, we demonstrate that stealthy hardware Trojans, as well as sophisticated modifications of P&R, can be detected with high confidence.

We consider multi-party information-theoretic private computation. Such computation inherently requires the use of local randomness by the parties, and the question of minimizing the total number of random bits used for given private computations has received considerable attention in the literature. In this work we are interested in another question: given a private computation, we ask how many of the players need to have access to a random source, and how many of them can be deterministic parties. We are further interested in the possible interplay between the number of random sources in the system and the total number of random bits necessary for the computation. We give a number of results. We first show that, perhaps surprisingly, $t$ players (rather than $t+1$) with access to a random source are sufficient for the information-theoretic $t$-private computation of any deterministic functionality over $n$ players for any $t<n/2$; by a result of (Kushilevitz and Mansour, PODC'96), this is best possible. This means that, counter intuitively, while private computation is impossible without randomness, it is possible to have a private computation even when the adversary can control all parties who can toss coins (and therefore sees all random coins). For randomized functionalities we show that $t+1$ random sources are necessary (and sufficient). We then turn to the question of the possible interplay between the number of random sources and the necessary number of random bits. Since for only very few settings in private computation meaningful bounds on the number of necessary random bits are known, we consider the AND function, for which some such bounds are known. We give a new protocol to $1$-privately compute the $n$-player AND function, which uses a single random source and $6$ random bits tossed by that source. This improves, upon the currently best known results (Kushilevitz et al., TCC'19), at the same time the number of sources and the number of random bits (KOPRT19 gives a $2$-source, $8$-bits protocol). This result gives maybe some evidence that for $1$-privacy, using the minimum necessary number of sources one can also achieve the necessary minimum number of random bits. We believe however that our protocol is of independent interest for the study of randomness in private computation.

This Paper proposes FssNN, a communication-efficient secure two-party computation framework for evaluating privacy-preserving neural network via function secret sharing (FSS) in semi-honest adversary setting. In FssNN, two parties with input data in secret sharing form perform secure linear computations using additive secret haring and non-linear computations using FSS, and obtain secret shares of model parameters without disclosing their input data. To decrease communication cost, we split the protocol into online and offline phases where input-independent correlated randomness is generated in offline phase while only lightweight ``non-cryptographic'' computations are executed in online phase. Specifically, we propose $\mathsf{BitXA}$ to reduce online communication in linear computation, DCF to reduce key size of the FSS scheme used in offline phase for nonlinear computation. To further support neural network training, we enlarge the input size of neural network to $2^{32}$ via ``MPC-friendly'' PRG. We implement the framework in Python and evaluate the end-to-end system for private training between two parties on standard neural networks. FssNN achieves on MNIST dataset an accuracy of 98.0%, with communication cost of 27.52GB and runtime of 0.23h per epoch in the LAN settings. That shows our work advances the state-of-the-art secure computation protocol for neural networks.

We put forth a new cryptographic primitive for securely computing inner-products in a scalable, non-interactive fashion: any party can broadcast a public (computationally hiding) encoding of its input, and store a secret state. Given their secret state and the other party's public encoding, any pair of parties can non-interactively compute additive shares of the inner-product between the encoded vectors. We give constructions of this primitive from a common template, which can be instantiated under either the LPN (with non-negligible correctness error) or the LWE (with negligible correctness error) assumptions. Our construction uses a novel twist on the standard non-interactive key exchange based on the Alekhnovich cryptosystem, which upgrades it to a non-interactive inner product protocol almost for free. In addition to being non-interactive, our constructions have linear communication (with constants smaller than all known alternatives) and small computation: using LPN or LWE with quasi-cyclic codes, we estimate that encoding a length-$2^{20}$ vector over a 32-bit field takes less that 2s on a standard laptop; decoding amounts to a single cheap inner-product. We show how to remove the non-negligible error in our LPN instantiation using a one-time, logarithmic-communication preprocessing. Eventually, we show to to upgrade its security to the malicious model using new sublinear-communication zero-knowledge proofs for low-noise LPN samples, which might be of independent interest.

This paper aims to provide a security analysis comparison between three popular instant messaging apps: Signal, WhatsApp and Telegram. The analysis will focus on the encryption protocols used by each app and the security features they offer. The paper will evaluate the strengths and weaknesses of each app, and provide a summary of their overall security posture. Additionally, this paper will discuss other considerations such as user base, data collection and usage policies, and other features which may impact the security of the apps. The results of this analysis will provide insights for individuals and organizations looking to choose a secure instant messaging app for their communication needs. In this paper we reviewed the main encryption standards and we compared the features, traffic analysis, protocols, performance and recent security breaches for WhatsApp, Signal and Telegram. The paper includes packet sniffing using Wireshark and Fiddler.

The purpose of this article is to present,illustrate and to put in evidence a new side- channel attack on RSA cryptosystem based on the generation of prime numbers. The vulnerability of the cryptosystem is spotted during the execution of the key generation step.The probability of success of the attack is around 10-15% in the case of realistic parameters

Public-key quantum money is a cryptographic proposal for using highly entangled quantum states as currency that is publicly verifiable yet resistant to counterfeiting due to the laws of physics. Despite significant interest, constructing provably-secure public-key quantum money schemes based on standard cryptographic assumptions has remained an elusive goal. Even proposing plausibly-secure candidate schemes has been a challenge. These difficulties call for a deeper and systematic study of the structure of public-key quantum money schemes and the assumptions they can be based on. Motivated by this, we present the first black-box separation of quantum money and cryptographic primitives. Specifically, we show that collision-resistant hash functions cannot be used as a black-box to construct public-key quantum money schemes where the banknote verification makes classical queries to the hash function. Our result involves a novel combination of state synthesis techniques from quantum complexity theory and simulation techniques, including Zhandry's compressed oracle technique.

The use of data as a product and service has given momentum to the extensive uptake of complex machine learning algorithms that focus on performing prediction with popular tree-based methods such as decision trees classifiers. With increasing adoption over a wide array of sensitive applications, a significant need to protect the confidentiality of the classifier model and user data is identified. The existing literature safeguards them using interactive solutions based on expensive cryptographic approaches, where an encrypted classifier model interacts with the encrypted queries and forwards the encrypted classification to the user. Adding to that, the state-of-art protocols for protecting the privacy of the model do not contain model-extraction attacks. We design an efficient virtual black-box obfuscator for binary decision trees and use the random oracle paradigm to analyze the security of our construction. To thwart model-extraction attacks, we restrict to evasive decision trees, as black-box access to the classifier does not allow a PPT adversary to extract the model. While doing so, we present an encoder for hiding parameters in an interval-membership function. Our exclusive goal behind designing the obfuscator is that, not only will the solution increase the class of functions that has cryptographically secure obfuscators, but also address the open problem of non-interactive prediction in privacy-preserving classification using computationally inexpensive cryptographic hash functions.

We propose a novel methodology to obtain $B$lind signatures that is fundamentally based on the idea of hiding part of the underlying plain signatures under a $Z$ero-knowledge argument of knowledge of the whole signature (hence the shorthand, $BZ$). Our proposal is necessarily non-black-box and stated in the random oracle model. We illustrate the technique by describing two instantiations: a classical setting based on the traditional discrete logarithm assumption, and a post-quantum setting based on the commutative supersingular isogeny Diffie-Hellman (CSIDH) assumption.

There is a line of 'lookup' protocols to show that all elements of a sequence $f\in{\mathbb F}^n$ are contained in a table $t\in{\mathbb F}^d$, for some field ${\mathbb F}$. Lookup has become an important primitive in Zero Knowledge Virtual Machines, and is used for range checks and other parts of the proofs of a correct program execution. In this note we give several variants of the protocol. We adapt it to the situation when there are multiple lookups with the same table (as is usually the case with range checks), and handle also 'bounded lookup' that caps the number of repetitions.

Fully Homomorphic Encryption enables arbitrary computations over encrypted data and it has a multitude of applications, e.g., secure cloud computing in healthcare or finance. Multi-Key Homomorphic Encryption (MKHE) further allows to process encrypted data from multiple sources: the data can be encrypted with keys owned by different parties. In this paper, we propose a new variant of MKHE instantiated with the TFHE scheme. Compared to previous attempts by Chen et al. and by Kwak et al., our scheme achieves computation runtime that is linear in the number of involved parties and it outperforms the faster scheme by a factor of 4.5-6.9x, at the cost of a slightly extended pre-computation. In addition, for our scheme, we propose and practically evaluate parameters for up to 128 parties, which enjoy the same estimated security as parameters suggested for the previous schemes (100 bits). It is also worth noting that our scheme—unlike the previous schemes—did not experience any error in any of our nine experiments, each running 1 000 trials.

We present several new heuristic algorithms to compute class polynomials and modular polynomials modulo a prime $P$. For that, we revisit the idea of working with supersingular elliptic curves. The best known algorithms to this date are based on ordinary curves, due to the supposed inefficiency of the supersingular case. While this was true a decade ago, the recent advances in the study of supersingular curves through the Deuring correspondence motivated by isogeny-based cryptography has provided all the tools to perform the necessary tasks efficiently. Our main ingredients are two new heuristic algorithms to compute the $j$-invariants of supersingular curves having an endomorphism ring contained in some set of isomorphism class of maximal orders. The first one is derived easily from the existing tools of isogeny-based cryptography, while the second introduces new ideas to perform that task efficiently for a big number of maximal orders. From there, we obtain two main results. First, we show that we can associate these two algorithms with some operations over the quaternion algebra ramified at $P$ and infinity to compute directly Hilbert and modular polynomials $\mod P$. In that manner, we obtain the first algorithms to compute Hilbert (resp. modular) polynomials modulo $P$ for a good portion of all (resp. all) primes $P$ with a complexity in $O(\sqrt{|D|})$ for the discriminant $D$ (resp. $O(\ell^2)$ for the level $\ell$). Due to the (hidden) complexity dependency on $P$, these algorithms do not outperform the best known algorithms for all prime $P$ but they still provide an asymptotic improvement for a range of prime going up to a bound that is sub-exponential in $|D|$ (resp. $\ell$). Second, we revisit the CRT method for both class and modular polynomials. We show that applying our second heuristic algorithm over supersingular curves to the CRT approach yields the same asymptotic complexity as the best known algorithms based on ordinary curves and we argue that our new approach might be more efficient in practice. The situation appears especially promising for modular polynomials, as our approach reduces the asymptotic cost of elliptic curve operations by a linear factor in the level $\ell$. We obtain an algorithm whose asymptotic complexity is now fully dominated by linear algebra and standard polynomial arithmetic over finite fields.

We introduce a new notion of {\em multiverse threshold signatures} (MTS). In an MTS scheme, multiple universes -- each defined by a set of (possibly overlapping) signers, their weights, and a specific security threshold -- can co-exist. A universe can be (adaptively) created via a non-interactive asynchronous setup. Crucially, each party in the multiverse holds constant-sized keys and releases compact signatures with size and computation time both independent of the number of universes. Given sufficient partial signatures over a message from the members of a specific universe, an aggregator can produce a short aggregate signature relative to that universe. We construct an MTS scheme building on BLS signatures. Our scheme is practical, and can be used to reduce bandwidth complexity and computational costs in decentralized oracle networks. As an example data point, consider a multiverse containing 2000 nodes and 100 universes (parameters inspired by Chainlink's use in the wild) each of which contains arbitrarily large subsets of nodes and arbitrary thresholds. Each node computes and outputs 1 group element as its partial signature; the aggregator performs under 0.7 seconds of work for each aggregate signature, and the final signature of size 192 bytes takes 6.4 ms (or 198K EVM gas units) to verify. For this setting, prior approaches when used to construct MTS, yield schemes that have one of the following drawbacks: (i) partial signatures that are 97$\times$ larger, (ii) have aggregation times 311$\times$ worse, or (iii) have signature size 39$\times$ and verification gas costs 3.38$\times$ larger. We also provide an open-source implementation and a detailed evaluation.

Since the invention of Bitcoin, cryptocurrencies have gained huge popularity. Crypto wallet, as the tool to store and manage the cryptographic keys, is the primary entrance for the public to access cryptocurrency funds. Deterministic wallet is an advanced wallet mech- anism that has been proposed to achieve some appealing virtues, such as low-maintenance, easy backup and recovery, supporting functionali- ties required by cryptocurrencies, and so on. But deterministic wallets still have a long way to be practical in quantum world, and there are also some gaps in the classic world, since there are the following prob- lems waiting to be solved. Firstly, the relying on the state, i.e., stateful. The stateful deterministic wallet scheme must internally maintain and keep refreshing synchronously a state which makes the implementation in practice become more complex. And once one of the states is leaked, thereafter the security notion of unlinkability is cannot be guaranteed (referred to as the weak security notion of forward unlinkability). The second problem is vulnerable. There are security shortfalls in previous works, they suffer a vulnerability when a minor fault happens (say, one derived key is compromised somehow), then the damage is not limited to the leaked derived key, instead, it spreads to the master key and the whole system collapses. Thirdly, the falling short in supporting hot/cold setting. The hot/cold setting is a widely adopted method to effectively reduce the exposure chance of secret keys and hence improving the se- curity of the deterministic wallet system. The last problem is the relying on the weak security notion of unforgeability, in which the adversary is only allowed to query and forge the signatures w.r.t. the public keys that were assigned by the challenger. In this work, we present a new deterministic wallet scheme in quantum world, which is stateless, supports hot/cold setting, satisfiies stronger security notions, and is more efficient. In particular, we reformalize the syntax and security models for deterministic wallets, capturing the func- tionality and security requirements imposed by the practice in cryptocur- rency. Then we propose a deterministic wallet construction and prove its security in the quantum random oracle model. Finally, we show our wal- let scheme is more practicable by analyzing an instantiation of our wallet scheme based on the signature scheme Falcon.

Multi-signature is a protocol where a set of signatures jointly sign a message so that the final signature is significantly shorter than concatenating individual signatures together. Recently, it finds applications in blockchain, where several users want to jointly authorize a payment through a multi-signature. However, in this setting, there is no centralized authority and it could suffer from a rogue key attack where the attacker can generate his own keys arbitrarily. Further, to minimize the storage on blockchain, it is desired that the aggregated public-key and the aggregated signature are both as short as possible. In this paper, we find a compiler that converts a kind of identification (ID) scheme (which we call a linear ID) to a multi-signature so that both the aggregated public-key and the aggregated signature have a size independent of the number of signers. Our compiler is provably secure. The advantage of our results is that we reduce a multi-party problem to a weakly secure two-party problem. We realize our compiler with two ID schemes. The first is Schnorr ID. The second is a new lattice-based ID scheme, which via our compiler gives the first regular lattice-based multi-signature scheme with key-and-signature compact without a restart during signing process.

Many applications in finance and healthcare need access to data from multiple organizations. While these organizations can benefit from computing on their joint datasets, they often cannot share data with each other due to regulatory constraints and business competition. One way mutually distrusting parties can collaborate without sharing their data in the clear is to use secure multiparty computation (MPC). However, MPC’s performance presents a serious obstacle for adoption as it is difficult for users who lack expertise in advanced cryptography to optimize. In this paper, we present Silph, a framework that can automatically compile a program written in a high-level language to an optimized, hybrid MPC protocol that mixes multiple MPC primitives securely and efficiently. Compared to prior works, our compilation speed is improved by up to 30000×. On various database analytics and machine learning workloads, the MPC protocols generated by Silph match or outperform prior work by up to 3.6×.

Two multivariate digital signature schemes, Rainbow and GeMSS, made it into the third round of the NIST PQC competition. However, either made its way to being a standard due to devastating attacks (in one case by Beullens, the other by Tao, Petzoldt, and Ding). How should multivariate cryptography recover from this blow? We propose that, rather than trying to fix Rainbow and HFEv- by introducing countermeasures, the better approach is to return to the classical Oil and Vinegar scheme. We show that, if parametrized appropriately, Oil and Vinegar still provides competitive performance compared to the new NIST standards by most measures (except for key size). At NIST security level 1, this results in either 128-byte signatures with 44 kB public keys or 96-byte signatures with 67 kB public keys. We revamp the state-of-the-art of Oil and Vinegar implementations for the Intel/AMD AVX2, the Arm Cortex-M4 microprocessor, the Xilinx Artix-7 FPGA, and the Armv8-A microarchitecture with the Neon vector instructions set.

We present SCALLOP: SCALable isogeny action based on Oriented supersingular curves with Prime conductor, a new group action based on isogenies of supersingular curves. Similarly to CSIDH and OSIDH, we use the group action of an imaginary quadratic order’s class group on the set of oriented supersingular curves. Compared to CSIDH, the main benefit of our construction is that it is easy to compute the class-group structure; this data is required to uniquely represent— and efficiently act by— arbitrary group elements, which is a requirement in, e.g., the CSI-FiSh signature scheme by Beullens, Kleinjung and Vercauteren. The index-calculus algorithm used in CSI-FiSh to compute the class-group structure has complexity L(1/2), ruling out class groups much larger than CSIDH-512, a limitation that is particularly problematic in light of the ongoing debate regarding the quantum security of cryptographic group actions. Hoping to solve this issue, we consider the class group of a quadratic order of large prime conductor inside an imaginary quadratic field of small discriminant. This family of quadratic orders lets us easily determine the size of the class group, and, by carefully choosing the conductor, even exercise significant control on it— in particular supporting highly smooth choices. Although evaluating the resulting group action still has subexponential asymptotic complexity, a careful choice of parameters leads to a practical speedup that we demonstrate in practice for a security level equivalent to CSIDH-1024, a parameter currently firmly out of reach of index-calculus-based methods. However, our implementation takes 35 seconds (resp. 12.5 minutes) for a single group-action evaluation at a CSIDH-512-equivalent (resp. CSIDH-1024-equivalent) security level, showing that, while feasible, the SCALLOP group action does not achieve realistically usable performance yet.

Critical and widely used cryptographic protocols have repeatedly been found to contain flaws in their design and their implementation. A prominent class of such vulnerabilities is logical attacks, i.e. attacks that solely exploit flawed protocol logic. Automated formal verification methods, based on the Dolev-Yao (DY) attacker, excel at finding such flaws, but operate only on abstract specification models. Fully automated verification of existing protocol implementations is today still out of reach. This leaves open whether widely used protocol implementations are secure. Unfortunately, this blind spot hides numerous attacks, notably recent logical attacks on widely used TLS implementations introduced by implementation bugs. We answer by proposing a novel and effective technique that we call DY model-guided fuzzing, which precludes logical attacks against protocol implementations. The main idea is to consider as possible test cases the set of abstract DY executions of the DY attacker, and use a mutation-based fuzzer to explore this set. The DY fuzzer concretizes each abstract execution to test it on the program under test. This approach enables reasoning at a more structural and security-related level of messages (e.g. decrypt a message and re-encrypt it with a different key) as opposed to random bit-level modifications that are much less likely to produce relevant logical adversarial behaviors. We implement a full-fledged and modular DY protocol fuzzer. We demonstrate its effectiveness by fuzzing three popular TLS implementations, resulting in the discovery of four novel vulnerabilities.

In recent works of Li the noisy subset product problem (also known as subset product with errors) was invented and applied to cryptography. To better understand its hardness, we give a quantum annealing algorithm for it. Our algorithm is the first algorithm for the problem. We also give the first quantum annealing algorithm for the subset product problem. The efficiencies of both algorithms rely on the fundamental efficiency of quantum annealing. At the end we give two lattice algorithms for both problems via solving the closest vector problem. The complexities of the lattice algorithms depend on the complexities of solving the closest vector problem in two special lattices. They are efficient when the special closest vector problems fall into the regime of bounded distance decoding problems that can be efficiently solved using existing methods based on the LLL algorithm or Babai's nearest plane algorithm.

Voting mechanisms allow the expression of the elections by a democratic approach. Any voting scheme must ensure, preferably in an efficient way, a series of safety measures such as confidentiality, integrity and anonymity. Since the 1980s, the concept of electronic voting became more and more of interest, being an advantageous or even necessary alternative for the organization of secure elections. In this paper, we give an overview for the e-voting mechanisms together with the security features they must fulfill. Then we focus on the blind signature paradigm, specifically on the Pairing Free Identity-Based Blind Signature Scheme with Message Recovery (PF-IDBS-MR). Our goal is to give a better understanding on the PF-IDBS-MR scheme by offering an adaptation on the standard voting protocol’s phases. More important, we analyze if the general security requirements and the recommendations proposed by the Council of Europe are met by the scheme.

We introduce incoercible digital signature schemes, a variant of a standard digital signature. Incoercible signatures enable signers, when coerced to produce a signature for a message chosen by an attacker, to generate fake signatures that are indistinguishable from real signatures, even if the signer is compelled to reveal their full history (including their secret signing keys and any randomness used to produce keys/signatures) to the attacker. Additionally, we introduce an authenticator that can detect fake signatures, which ensures that coercion is identified. We present a formal security model for incoercible signature schemes that comprises an established definition of unforgeability and captures new notions of weak receipt-freeness, strong receipt-freeness and coercion-resistance. We demonstrate that an incoercible signature scheme can be viewed as a transformation of any generic signature scheme. Indeed, we present two incoercible signature scheme constructions that are built from a standard signature scheme and a sender-deniable encryption scheme. We prove that our first construction satisfies coercion-resistance, and our second satisfies strong receipt-freeness. We conclude by presenting an extension to our security model: we show that our security model can be extended to the designated verifier signature scheme setting in an intuitive way as the designated verifier can assume the role of the authenticator and detect coercion during the verification process.

In practical operational networks, it is essential to validate path integrity, especially when untrusted intermediate nodes are from numerous network infrastructures operated by several network authorities. Current solutions often reveal the entire path to all parties involved, which may potentially expose the network structures to malicious intermediate attackers. Additionally, there is no prior work done to provide a systematic approach combining the complete lifecycle of packet delivery, i.e., path slicing, path validation and path rerouting, leaving these highly-intertwined modules completely separated. In this work, we present a decentralized privacy-preserving path validation system 𝑃3𝑉 that integrates our novel path validation protocol with an efficient path slicing algorithm and a malice-resilient path rerouting mechanism. Specifically, leveraging Non-Interactive Zero-Knowledge proofs, our path validation protocol XOR-Hash-NIZK protects the packet delivery tasks against information leakage about multi-hop paths and potentially the underlying network infrastructures. We implemented and evaluated our system on a state-of-the-art 5G Dispersed Computing Testbed simulating a multi-authority network. Our results show that while preserving the privacy of paths and nodes and enhancing the security of network service, our system optimizes the performance trade-off between network service quality and security/privacy.

An important research direction in secure multi-party computation (MPC) is to improve the efficiency of the protocol. One idea that has recently received attention is to consider a slightly weaker security model than full malicious security -- the so-called setting of $\textit{covert security}$. In covert security, the adversary may cheat but only is detected with certain probability. Several works in covert security consider the offline/online approach, where during a costly offline phase correlated randomness is computed, which is consumed in a fast online phase. State-of-the-art protocols focus on improving the efficiency by using a covert offline phase, but ignore the online phase. In particular, the online phase is usually assumed to guarantee security against malicious adversaries. In this work, we take a fresh look at the offline/online paradigm in the covert security setting. Our main insight is that by weakening the security of the online phase from malicious to covert, we can gain significant efficiency improvements during the offline phase. Concretely, we demonstrate our technique by applying it to the online phase of the well-known TinyOT protocol (Nielsen et al., CRYPTO '12). The main observation is that by reducing the MAC length in the online phase of TinyOT to $t$ bits, we can guarantee covert security with a detection probability of $1- \frac{1}{2^t}$. Since the computation carried out by the offline phase depends on the MAC length, shorter MACs result in a more efficient offline phase and thus speed up the overall computation. Our evaluation shows that our approach reduces the communication complexity of the offline protocol by at least 35% for a detection rate up to $\frac{7}{8}$. In addition, we present a new generic composition result for analyzing the security of online/offline protocols in terms of concrete security.

Applying the pothole method on the factors of numbers of the form $2^n-1$, we prove the inequality $$\iota(2^n-1)\leq n-1+\iota(n)$$ where $\iota(n)$ denotes the length of the shortest addition chain producing $n$.

This paper presents a new profiling side-channel attack on the signature scheme CRYSTALS-Dilithium, which has been selected by the NIST as the new primary standard for quantum-safe digital signatures. This algorithm has a constant-time implementation with consideration for side-channel resilience. However, it does not protect against attacks that exploit intermediate data leakage. We exploit such a leakage on a vector generated during the signing process and whose costly protection by masking is a matter of debate. We design a template attack that enables us to efficiently predict whether a given coefficient in one coordinate of this vector is zero or not. Once this value has been completely reconstructed, one can recover, using linear algebra methods, part of the secret key that is sufficient to produce universal forgeries. While our paper deeply discusses the theoretical attack path, it also demonstrates the validity of the assumption regarding the required leakage model, from practical experiments with the reference implementation on an ARM Cortex-M4.

Homomorphic encryption (HE) is one of the most promising techniques for privacy-preserving computations, especially the word-wise HE schemes that allow batched computations over ciphertexts. However, the high computational overhead hinders the deployment of HE in real-word applications. The GPUs are often used to accelerate the execution in such scenarios, while the performance of different HE schemes on the same GPU platform is still absent. In this work, we implement three word-wise HE schemes BGV, BFV, and CKKS on GPU, with both theoretical and engineering optimizations. We optimize the hybrid key-switching technique, reducing the computational and memory overhead of this procedure. We explore several kernel fusing strategies to reuse data, which reduces the memory access and IO latency, and improves the overall performance. By comparing with the state-of-the-art works, we demonstrate the effectiveness of our implementation. Meanwhile, we present a framework that finely integrates our implementation of the three schemes, covering almost all scheme functions and homomorphic operations. We optimize the management of pre-computation, RNS bases and memory in the framework, to provide efficient and low-latency data access and transfer. Based on this framework, we provide a thorough benchmark of the three schemes, which can serve as a reference for scheme selection and implementation in constructing privacy-preserving applications.

On-line/off-line encryption schemes enable the fast encryption of a message from a pre-computed coupon. The paradigm was put forward in the case of digital signatures. This work introduces a compact public-key additively homomorphic encryption scheme. The scheme is semantically secure under the decisional composite residuosity (DCR) assumption. Compared to Paillier cryptosystem, it merely requires one or two integer additions in the on-line phase and no increase in the ciphertext size. This work also introduces a compact on-line/off-line trapdoor commitment scheme featuring the same fast on-line phase. Finally, applications to chameleon signatures are presented.

The goals of cryptography are achieved using mathematically strong crypto-algorithms, which are adopted for securing data and communication. Even though the algorithms are mathematically secure, the implementation of these algorithms may be vulnerable to side-channel attacks such as timing and power analysis attacks. One of the effective countermeasures against such attacks is Threshold Implementation(TI). However, TI realization in crypto-device introduces hardware complexity, so it shall not be suitable for resource-constrained devices. Therefore, there is a need for efficient and effective countermeasure techniques for resource-constrained devices. In this work, we propose a lightweight countermeasure using an Arbiter Physical Unclonable Function (A-PUF) to obfuscate intermediate values in the register for rolled and unrolled implementation of Advanced Encryption Standard (AES). The countermeasure is realized in rolled (iterative) implementation of AES in a 65nm Field Programmable Gate Array (FPGA). We have analyzed the security strength and area of the obfuscated AES using A-PUF and compared it with conventional (rolled AES) and masked TI of AES. Further, we have illustrated the effectiveness of pre-charge and neutralizing countermeasures to strengthen the side channel resistance. We have discussed the complexity of mounting a side channel and modeling attacks on obfuscated AES using A-PUF.

This study presents a proof-of-concept for a cognitive-based authentication system that uses an individual's writing style as a unique identifier to grant access to a system. A machine learning SVM model was trained on these features to distinguish between texts generated by each user. The stylometric feature vector was then used as an input to a key derivation function to generate a unique key for each user. The experiment results showed that the developed system achieved up to 87.42\% accuracy in classifying texts as written, and the generated keys were found to be secure and unique. We explore the intersection between natural intelligence, cognitive science, and cryptography, intending to develop a cognitive cryptography system. The proposed system utilizes behavioral features from linguistic-biometric data to detect and classify users through stylometry. This information is then used to generate a cryptographic key for authentication, providing a new level of security in access control. The field of cognitive cryptography is relatively new and has yet to be fully explored, making this research particularly relevant and essential. Through our study, we aim to contribute to understanding the potential of cognitive cryptography and its potential applications in securing access to sensitive information.

Ransomware is a malware that employs encryption to hold a victim's data, causing irreparable loss and monetary incentives to individuals or business organizations. The occurrence of ransomware attacks has been increasing significantly and as the attackers are investing more creativity and inventiveness into their threats, the struggle of fighting against ill-themed activities has become more difficult and even time and energy-draining. Therefore, recent researches try to shed some light on combining machine learning with defense mechanisms for detecting this type of malware. Machine learning allows anti-ransomware systems to become more accurate at predicting outcomes or behaviors of the attacks and is vastly used in the advanced research of cybersecurity. In this paper we analyze how machine learning can improve malware recognition in order to stand against critical security issues, giving a brief, yet comprehensive overview of this thriving topic in order to facilitate future research. We also briefly present the most important events of 2022 in terms of ransomware attacks, providing details about the ransoms demanded.

Most cryptographic protocols model a player’s knowledge of secrets in a simple way. Informally, the player knows a secret in the sense that she can directly furnish it as a (private) input to a protocol, e.g., to digitally sign a message. The growing availability of Trusted Execution Environments (TEEs) and secure multiparty computation, however, undermines this model of knowledge. Such tools can encumber a secret sk and permit a chosen player to access sk conditionally, without actually knowing sk. By permitting selective access to sk by an adversary, encumbrance of secrets can enable vote-selling in cryptographic voting schemes, illegal sale of credentials for online services, and erosion of deniability in anonymous messaging systems. Unfortunately, existing proof-of-knowledge protocols fail to demonstrate that a secret is unencumbered. We therefore introduce and formalize a new notion called complete knowledge (CK). A proof (or argument) of CK shows that a prover does not just know a secret, but also has fully unencumbered knowledge, i.e., unrestricted ability to use the secret. We introduce two practical CK schemes that use special-purpose hardware, specifically TEEs and off-the-shelf mining ASICs. We prove the security of these schemes and explore their practical deployment with a complete, end-to-end prototype that supports both. We show how CK can address encumbrance attacks identified in previous work. Finally, we introduce two new applications enabled by CK that involve proving ownership of blockchain assets.

State-of-the-art sensors for measuring FPGA voltage fluctuations are time-to-digital converters (TDCs). They allow detecting voltage fluctuations in the order of a few nanoseconds. The key building component of a TDC is a delay line, typically implemented as a chain of fast carry propagation multiplexers. In FPGAs, the fast carry chains are constrained to dedicated logic and routing, and need to be routed strictly vertically. In this work, we present an alternative approach to designing on-chip voltage sensors, in which the FPGA routing resources replace the carry logic. We present three variants of what we name a routing delay sensor (RDS): one vertically constrained, one horizontally constrained, and one free of any constraints. We perform a thorough experimental evaluation on both the Sakura-X side-channel evaluation board and the Alveo U200 datacenter card, to evaluate the performance of the RDS sensors in the context of a remote power side-channel analysis attack. The results show that our best RDS implementation in most cases outperforms the TDC. On average, for breaking the full 128-bit key of an AES-128 cryptographic core, an adversary requires 35% fewer side-channel traces when using the RDS than when using the TDC. Besides making the attack more effective, given the absence of the placement and routing constraint, the RDS sensor is also easier to deploy.

SPHINCS+ is a hash-based digital signature scheme that was selected by NIST in their post-quantum cryptography standardization process. The establishment of a universal forgery on the seminal scheme SPHINCS was shown to be feasible in practice by injecting a fault when the signing device constructs any non-top subtree. Ever since the attack has been made public, little effort was spent to protect the SPHINCS family against attacks by faults. This paper works in this direction in the context of SPHINCS+ and analyzes the current algorithms that aim to prevent fault-based forgeries. First, the paper adapts the original attack to SPHINCS+ reinforced with randomized signing and extends the applicability of the attack to any combination of faulty and valid signatures. Considering the adaptation, the paper then presents a thorough analysis of the attack. In particular, the analysis shows that, with high probability, the security guarantees of SPHINCS+ significantly drop when a single random bit flip occurs anywhere in the signing procedure and that the resulting faulty signature cannot be detected with the verification procedure. The paper shows both in theory and experimentally that the countermeasures based on caching the intermediate W-OTS+s offer a marginally greater protection against unintentional faults, and that such countermeasures are circumvented with a tolerable number of queries in an active attack. Based on these results, the paper recommends real-world deployments of SPHINCS+ to implement redundancy checks.

The use of traditional cryptography based on symmetric keys has been replaced with the revolutionary idea discovered by Diffie and Hellman in 1976 that fundamentally changed communication systems by ensuring a secure transmission of information over an insecure channel. Nowadays public key cryptography is frequently used for authentication in e-commerce, digital signatures and encrypted communication. Most of the public key cryptosystems used in practice are based on integer factorization (the famous RSA cryptosystem proposed by Rivest, Shamir and Adlemann), respectively on the discrete logarithm (in finite curves or elliptic curves). However these systems suffer from two potential drawbacks like efficiency because they must use large keys to maintain security and of course security breach with the advent of the quantum computer as a result of Peter Shor's discovery in 1999 of the polynomial algorithm for solving problems such factorization of integers and discrete logarithm.

TRNG is an essential component for security applications. A vulnerable TRNG could be exploited to facilitate potential attacks or be related to a reduced key space, and eventually results in a compromised cryptographic system. A digital FIRO-/GARO-based TRNG with high throughput and high entropy rate was introduced by Jovan Dj. Golić (TC’06). However, the fact that periodic oscillation is a main failure of FIRO-/GARO-based TRNGs is noticed in the paper (Markus Dichtl, ePrint’15). We verify this problem and estimate the consequential entropy loss using Lyapunov exponents and the test suite of the NIST SP 800-90B standard. To address the problem of periodic oscillations, we propose several implementation guidelines based on a gate-level model, a design methodology to build a reliable GARO-based TRNG, and an online test to improve the robustness of FIRO-/GARO-based TRNGs. The gate-level implementation guidelines illustrate the causes of periodic oscillations, which are verified by actual implementation and bifurcation diagram. Based on the design methodology, a suitable feedback polynomial can be selected by evaluating the feedback polynomials. The analysis and understanding of periodic oscillation and FIRO-/GARO-based TRNGs are deepened by delay adjustment. A TRNG with the selected feedback polynomial may occasionally enter periodic oscillations, due to active attacks and the delay inconstancy of implementations. This inconstancy might be caused by self-heating, temperature and voltage fluctuation, and the process variation among different silicon chips. Thus, an online test module, as one indispensable component of TRNGs, is proposed to detect periodic oscillations. The detected periodic oscillation can be eliminated by adjusting feedback polynomial or delays to improve the robustness. The online test module is composed of a lightweight and responsive detector with a high detection rate, outperforming the existing detector design and statistical tests. The areas, power consumptions and frequencies are evaluated based on the ASIC implementations of a GARO, the sampling circuit and the online test module. The gate-level implementation guidelines promote the future establishment of the stochastic model of FIRO-/GARO-based TRNGs with a deeper understanding.

We propose a threshold encryption scheme with two-party decryption, where one of the keyshares may be stored and used in a device that is able to provide only weak security for it. We state the security properties the scheme needs to have to support such use-cases, and construct a scheme with these properties.

Designing an efficient solution for Byzantine broadcast is an important problem for many distributed computing and cryptographic tasks. There have been many attempts to achieve sub-quadratic communication complexity in several directions, both in theory and practice, all with pros and cons. This paper initiates the study of another attempt: improving the amortized communication complexity of multi-shot Byzantine broadcast. Namely, we try to improve the average cost when we have sequential multiple broadcast instances. We present a protocol that achieves optimal amortized linear complexity under an honest majority. Our core technique is to efficiently form a network for disseminating the sender's message by keeping track of dishonest behaviors over multiple instances. We also generalize the technique for the dishonest majority to achieve amortized quadratic communication complexity.

Generating supersingular elliptic curves of unknown endomorphism ring has been a problem vexing isogeny-based cryptographers for several years. A recent development has proposed a trusted setup protocol to generate such a curve, where each participant generates and proves knowledge of an isogeny. Thus, the construction of efficient proofs of knowledge of isogeny has developed new interest. Historically, the isogeny community has assumed that obtaining isogeny proofs of knowledge from generic proof systems, such as zkSNARKs, was not a practical approach. We contribute the first concrete result in this area by applying Aurora (EUROCRYPT'19), Ligero (CCS'17) and Limbo (CCS'21) to an isogeny path relation, and comparing their performance to a state-of-the-art, tailor-made protocol for the same relation. In doing so, we show that modern generic proof systems are competitive when applied to isogeny assumptions, and provide an order of magnitude ($10\textrm{-}30\times$) improvement to proof and verification times, with similar proof sizes. In addition, these proofs provide a stronger notion of soundness, and statistical zero-knowledge; a property that has only recently been achieved in isogeny PoKs. Independently, this technique shows promise as a component in the design of future isogeny-based or other post-quantum protocols.

Troika is a sponge-based hash function designed by Kölbl, Tischhauser, Bogdanov and Derbez in 2019. Its specificity is that it is defined over $\mathbb{F}_3$ in order to be used inside IOTA’s distributed ledger but could also serve in all settings requiring the generation of ternary randomness. To be used in practice, Troika needs to be proven secure against state-of-the-art cryptanalysis. However, there are today almost no analysis tools for ternary designs. In this article we take a step in this direction by analyzing the propagation of differential trails of Troika and by providing bounds on the weight of its trails. For this, we adapt a well-known framework for trail search designed for KECCAK and provide new advanced techniques to handle the search on $\mathbb{F}_3$. Our work demonstrates that providing analysis tools for non-binary designs is a highly non-trivial research direction that needs to be enhanced in order to better understand the real security offered by such non-conventional primitives.

Today, resistance to physical defaults is a necessary criterion for masking schemes. In this context, the focus has long been on designing masking schemes guaranteeing security in the presence of glitches. Sadly, immunity against glitches increases latency as registers must stop the glitch propagation. Previous works could reduce the latency by removing register stages but only by impractically increasing the circuit area. Nevertheless, some relatively new attempts avoid glitches by applying DRP logic styles. Promising works in this area include LMDPL, SESYM - both presented at CHES - and Self-Timed Masking - presented at CARDIS - enabling to mask arbitrary circuits with only one cycle latency. However, even if glitches no longer occur, there are other physical defaults that may violate the security of a masked circuit. Imbalanced delay of dual rails is a known problem for the security of DRP logic styles such as WDDL but not covered in formal security models. In this work, we fill the gap by presenting the delay-extended probing security model, a generalization of the popular glitch-extended probing model, covering imbalanced delays. We emphasize the importance of such a model by a formal and practical security analysis of LMDPL, SESYM, and Self-Timed Masking. While we formally prove the delay-extended security of LMDPL and Self-Timed Masking, we show that SESYM fails to provide security under our defined security model what causes detectable leakage through experimental evaluations. Hence, as the message of this work, avoiding glitches in combination with d-probing security is not enough to guarantee physical security in practice.

A decisive contribution to the all-embracing protection of cryptographic software, especially on embedded devices, is the protection against SCA attacks. Masking countermeasures can usually be integrated into the software during the design phase. In theory, this should provide reliable protection against such physical attacks. However, the correct application of masking is a non-trivial task which often causes even experts to make mistakes. In addition to human-caused errors, micro-architectural CPU effects can lead even a seemingly theoretically correct implementation to fail satisfying the desired level of security in practice. This originates from different components of the underlying CPU which complicates the tracing of leakage back to a particular source and hence avoids to make general and device-independent statements about its security. In this work, we adapt PROLEAD for the evaluation of masked software, which has recently been presented at CHES 2022 and originally developed as a simulation-based tool to evaluate masked hardware designs. We enable to transfer the already known benefits of PROLEAD into the software world. These include (1) evaluation of larger designs compared to the state of the art, e.g. a full AES masked implementation, and (2) formal verification under the well-established robust probing security model. In short, together with an abstraction model for the micro-architecture, the robust probing model allows us to efficiently detect micro-architectural leakages while being independent of a concrete CPU design. As a concrete result, using PROLEAD_SW we evaluated the security of several publicly available masked software implementations and revealed multiple vulnerabilities.

In this note we explain how to compute $n$ KZG proofs for a polynomial of degree $d$ in time superlinear of $(t+d)$. Our technique is used in lookup arguments and vector commitment schemes.

The applicability of lattice reduction to a wide variety of cryptographic situations makes it an important part of the cryptanalyst's toolbox. Despite this, the construction of lattices and use of lattice reduction algorithms for cryptanalysis continue to be somewhat difficult to understand for beginners. This tutorial aims to be a gentle but detailed introduction to lattice-based cryptanalysis targeted towards the novice cryptanalyst with little to no background in lattices. We explain some popular attacks through a conceptual model that simplifies the various components of a lattice attack.

A single-leader election (SLE) is a way to elect one leader randomly among the parties in a distributed system. If the leader is secret (i.e., unpredictable) then it is called a secret single leader election (SSLE). In this paper, we model the security of SLE in the universally composable (UC) model. Our model is adaptable to various unpredictability levels for leaders that an SLE aims to provide. We construct an SLE protocol that we call semi-anonymous single leader election (SASLE). We show that SASLE is secure against adaptive adversaries in the UC model. SASLE provides a good amount of unpredictability level to most of the honest leaders while it does not provide unpredictability to the rest of them. In this way, we obtain better communication overhead by comparing the existing SSLE protocols. In the end, we construct a PoS-protocol (Sassafras) which deploys SASLE to elect the block producers. Sassafras benefits from the efficiency of SASLE and gains significant security both to grinding attacks and the private attack as shown by Azouvi and Cappelletti (ACM AFT 2021) because it elects a single block producer.

In Private Set Intersection protocols (PSIs), a non-empty result always reveals something about the private input sets of the parties. Moreover, in various variants of PSI, not all parties necessarily receive or are interested in the result. Nevertheless, to date, the literature has assumed that those parties who do not receive or are not interested in the result still contribute their private input sets to the PSI for free, although doing so would cost them their privacy. In this work, for the first time, we propose a multi-party PSI, called “Anesidora”, that rewards parties who contribute their private input sets to the protocol. Anesidora is efficient; it mainly relies on symmetric key primitives and its computation and communication complexities are linear with the number of parties and set cardinality. It remains secure even if the majority of parties are corrupted by active colluding adversaries.

End-to-end encryption (E2EE) prevents online services from accessing user content. This important security property is also an obstacle for content moderation methods that involve content analysis. The tension between E2EE and efforts to combat child sexual abuse material (CSAM) has become a global flashpoint in encryption policy, because the predominant method of detecting harmful content---server-side perceptual hash matching on plaintext images---is unavailable. Recent applied cryptography advances enable private hash matching (PHM), where a service can match user content against a set of known CSAM images without revealing the hash set to users or nonmatching content to the service. These designs, especially a 2021 proposal for identifying CSAM in Apple's iCloud Photos service, have attracted widespread criticism for creating risks to security, privacy, and free expression. In this work, we aim to advance scholarship and dialogue about PHM by contributing new cryptographic methods for system verification by the general public. We begin with motivation, describing the rationale for PHM to detect CSAM and the serious societal and technical issues with its deployment. Verification could partially address shortcomings of PHM, and we systematize critiques into two areas for auditing: trust in the hash set and trust in the implementation. We explain how, while these two issues cannot be fully resolved by technology alone, there are possible cryptographic trust improvements. The central contributions of this paper are novel cryptographic protocols that enable three types of public verification for PHM systems: (1) certification that external groups approve the hash set, (2) proof that particular lawful content is not in the hash set, and (3) eventual notification to users of false positive matches. The protocols that we describe are practical, efficient, and compatible with existing PHM constructions.

A distributed point function (DPF) (Gilboa-Ishai, Eurocrypt 2014) is a cryptographic primitive that enables compressed additive secret-sharing of a secret weight-1 vector across two or more servers. DPFs support a wide range of cryptographic applications, including efficient private information retrieval, secure aggregation, and more. Up to now, the study of DPFs was restricted to the computational security setting, relying on one-way functions. This assumption is necessary in the case of a dishonest majority. We present the first statistically private 3-server DPF for domain size $N$ with subpolynomial key size $N^{o(1)}$. We also present a similar perfectly private 4-server DPF. Our constructions offer benefits over their computationally secure counterparts, beyond the superior security guarantee, including better computational complexity and better protocols for distributed key generation, all while having comparable communication complexity for moderate-sized parameters.

This paper describes a formalization of the specification and the algorithm of the cryptographic scheme CRYSTALS-KYBER as well as the verification of its (1 − δ)-correctness proof. During the formalization, a problem in the correctness proof was uncovered. In order to amend this issue, a necessary property on the modulus parameter of the CRYSTALS-KYBER algorithm was introduced. This property is already implicitly fulfilled by the structure of the modulus prime used in the number theoretic transform (NTT). The NTT and its convolution theorem in the case of CRYSTALS-KYBER was formalized as well. The formalization was realized in the theorem prover Isabelle.

We are applying Fermat’s factorization algorithm to sets of public RSA keys. Fermat’s factorization allows efficiently calculating the prime factors of a composite number if the difference between the two primes is small. Knowledge of the prime factors of an RSA public key allows efficiently calculating the private key. A flawed RSA key generation function that produces close primes can therefore be attacked with Fermat’s factorization. We discovered a small number of vulnerable devices that generate such flawed RSA keys in the wild. These affect devices from two printer vendors - Canon and Fuji Xerox. Both use an underlying cryptographic module by Rambus.

In this paper, we investigate the security of several recent MAC constructions with provable security beyond the birthday bound (called BBB MACs) in the quantum setting. On the one hand, we give periodic functions corresponding to targeted MACs (including PMACX, PMAC with parity, HPxHP, and HPxNP), and we can recover secret states using Simon algorithm, leading to forgery attacks with complexity O(n). This implies our results realize an exponential speedup compared with the classical algorithm. Note that our attacks can even break some optimally secure MACs, such as mPMAC+-f, mPMAC+-p1, mPMAC+-p2, mLightMAC+-f, etc. On the other hand, we construct new hidden periodic functions based on SUM-ECBC-like MACs: SUM-ECBC, PolyMAC, GCM-SIV2, and 2K-ECBC−Plus, where periods reveal the information of the secret key. Then, by applying Grover-meets-Simon algorithm to specially constructed functions, we can recover full keys with O(2^(n/2)n) or O(2^(m/2)n) quantum queries, where n is the message block size and m is the length of the key. Considering the previous best quantum attack, our key-recovery attacks achieve a quadratic speedup.

Functional Encryption (FE) is a modern cryptographic technique that allows users to learn only a specific function of the encrypted data and nothing else about its actual content. While the first notions of security in FE revolved around the privacy of the encrypted data, more recent approaches also consider the privacy of the computed function. While in the public key setting, only a limited level of function-privacy can be achieved, in the private-key setting privacy potential is significantly larger. However, this potential is still limited by the lack of rich function families. For this work, we started by identifying the limitations of the current state-of-the-art approaches which, in its turn, allowed us to consider a new threat model for FE schemes. To the best of our knowledge, we here present the first attempt to quantify the leakage during the execution of an FE scheme. By leveraging the functionality offered by Trusted Execution Environments, we propose a construction that given any message-private functional encryption scheme yields a function-private one. Finally, we argue in favour of our construction's applicability on constrained devices by showing that it has low storage and computation costs.

The Feistel construction is one of the most studied ways of building block ciphers. Several generalizations were proposed in the literature, leading to the Generalized Feistel Network (GFN) construction, in which the round function operates on each pair of blocks in parallel until all branches are permuted. At FSE'10, Suzaki and Minematsu studied the diffusion of such construction, raising the question of how many rounds are required so that each block of the ciphertext depends on all blocks of the plaintext. Exhausting all possible permutations up to 16 blocks, they observed that there were always optimal permutations mapping even-number input blocks to odd-number output blocks and vice versa. Recently, both Cauchois et al. and Derbez et al. proposed new algorithms to build optimal even-odd permutations for up to 36 blocks. In this paper, we present a new algorithm based on iterative path building to search for optimal Feistel permutation. This algorithm is much faster in exhausting optimal non-even-odd permutations than all the previous approaches. Our first result is a computational proof that no non-even-odd permutation reaches a better diffusion round than optimal even-odd permutations up to 32 blocks. Furthermore, it is well known that permutations with an optimal diffusion round do not always lead to optimal permutations against differential cryptanalysis. We investigate several new criteria to build permutations leading to more secure GFN.

Embedded systems are a cornerstone of the ongoing digitization of our society, ranging from expanding markets around IoT and smart-X devices over to sensors in autonomous driving, medical equipment or critical infrastructures. Since a vast amount of embedded systems are safety-critical (e.g., due to their operation site), security is a necessity for their operation. However, unlike mobile, desktop, and server systems, where adversaries typically only act have remote access, embedded systems typically face attackers with physical access. Thus embedded system require an additional set of defense techniques, preferably leveraging hardware acceleration to minimize the impact on their stringent operation constraints. Over the last decade numerous defenses have been explored, however, they have often been analyzed in isolation. In this work, we first systematically analyze the state of the art in defenses for both software exploitation and fault attacks on embedded systems. We then carefully design a holistic instruction set extension to augment the RISC-V instruction set architecture with instructions to deter against the threats analyzed in this work. Moreover we implement our design using the gem5 simulator system and a binary translation approach to arm software with our instruction set extension. Finally, we evaluate performance overhead on the MiBench2 benchmark suite. Our evaluation demonstrates a ROM overhead increase of 20% to defeat the aforementioned attacks.

Deep learning techniques have been widely applied to side-channel analysis (SCA) in recent years and shown better performance compared with traditional methods. However, there has been little research dealing with deep learning techniques in fault analysis to date. This article undertakes the first study to introduce deep learning techniques into fault analysis to perform key recovery. We investigate the application of multi-layer perceptron (MLP) and convolutional neural network (CNN) in persistent fault analysis (PFA) and propose deep learning-based persistent fault analysis (DLPFA). DLPFA is first applied to advanced encryption standard (AES) to verify its availability. Then, to push the study further, we extend DLPFA to PRESENT, which is a lightweight substitution–permutation network (SPN)-based block cipher. The experimental results show that DLPFA can handle random faults and provide outstanding performance with a suitable selection of hyper-parameters.

It is known that the Scholz conjecture on addition chains is true for all integers n with ℓ(2n) = ℓ(n) + 1. There exists infinitely many integers with ℓ(2n) ≤ ℓ(n) and we don’t know if the conjecture still holds for them. The conjecture is also proven to hold for integers n with v(n) ≤ 5 and for infinitely many integers with v(n) = 6. There is no specific results on integers with v(n) = 7. In [14], an infinite list of integers satisfying ℓ(n) = ℓ(2n) and v(n) = 7 is given by Thurber. In this paper, we prove that the conjecture holds for all of them.

Hyperparameter tuning represents one of the main challenges in deep learning-based profiling side-channel analysis. For each different side-channel dataset, the typical procedure to find a profiling model is applying hyperparameter tuning from scratch. The main reason is that side-channel measurements from various targets contain different underlying leakage distributions. Consequently, the same profiling model hyperparameters are usually not equally efficient for other targets. This paper considers autoencoders for dimensionality reduction to verify if encoded datasets from different targets enable the portability of profiling models and architectures. Successful portability reduces the hyperparameter tuning efforts as profiling model tuning is eliminated for the new dataset, and tuning autoencoders is simpler. We first search for the best autoencoder for each dataset and the best profiling model when the encoded dataset becomes the training set. Our results show no significant difference in tuning efforts using original and encoded traces, meaning that encoded data reliably represents the original data. Next, we verify how portable is the best profiling model among different datasets. Our results show that tuning autoencoders enables and improves portability while reducing the effort in hyperparameter search for profiling models. Lastly, we present a transfer learning case where dimensionality reduction might be necessary if the model is tuned for a dataset with fewer features than the new dataset. In this case, tuning of the profiling model is eliminated and training time reduced.

Optimizing the quantum circuit for implementing Advanced Encryption Standard (AES) is crucial for estimating the necessary resources in attacking AES by Grover algorithm. Previous studies have reduced the number of qubits required for the quantum circuits of AES-128/-192/-256 from 984/1112/1336 to 270/334/398, which is close to the optimal value of 256/320/384. It becomes a challenging task to further optimize them. Aiming at this task, we find a method about how the quantum circuit of AES S-box can be designed with the help of automation tool LIGHTER-R. Particularly, the multiplicative inversion in F_2^8, which is the main part of S-box, is converted into the multiplicative inversion (and multiplication) in F_2^4, then the latter can be implemented by LIGHTER-R because its search space is small enough. By this method, we construct the quantum circuits of S-box for mapping |a>|0> to |a>|S(a)> and |a>|b> to |a>|b+S(a)> with 20 qubits instead of 22 in the previous studies. Besides, we introduce new techniques to reduce the number of qubits required by the S-box circuit for mapping |a> to |S(a)>from 22 in the previous studies to 16. Accordingly, we synthesize the quantum circuits of AES-128/-192/-256 with 264/328/392 qubits, which implies a new record.

We consider actions of a group or a semigroup on a set, which generalize the setup of discrete logarithm based cryptosystems. Such cryptographic group actions have gained increasing attention recently in the context of isogeny-based cryptography. We introduce generic algorithms for the semigroup action problem and discuss lower and upper bounds. Also, we investigate Pohlig-Hellman type attacks in a general sense. In particular, we consider reductions provided by non-invertible elements in a semigroup, and we deal with subgroups in the case of group actions.

The learning with errors (LWE) assumption is a powerful tool for building encryption schemes with useful properties, such as plausible resistance to quantum computers, or support for homomorphic computations. Despite this, essentially the only method of achieving threshold decryption in schemes based on LWE requires a modulus that is superpolynomial in the security parameter, leading to a large overhead in ciphertext sizes and computation time. In this work, we propose a (fully homomorphic) encryption scheme that supports a simple $t$-out-of-$n$ threshold decryption protocol while allowing for a polynomial modulus. The main idea is to use the Rényi divergence (as opposed to the statistical distance as in previous works) as a measure of distribution closeness. This comes with some technical obstacles, due to the difficulty of using the Rényi divergence in decisional security notions such as standard semantic security. We overcome this by constructing a threshold scheme with a weaker notion of one-way security and then showing how to transform any one-way threshold scheme into one guaranteeing semantic security.

Non-interactive zero-knowledge (NIZK) proof systems are often constructed based on cryptographic assumptions. In this paper, we propose the first unconditionally secure NIZK system in the AC0-fine-grained setting. More precisely, our NIZK system has perfect soundness for all adversaries and unconditional zero-knowledge for AC0 adversaries, namely, an AC0 adversary can only break the zero-knowledge property with negligible probability unconditionally. At the core of our construction is an OR-proof system for satisfiability of 1 out of polynomial many statements.

Micciancio and Sorrel (ICALP 2018) proposed a bootstrapping algorithm that can refresh many messages at once with sublinearly many homomorphic operations per message. However, despite the attractive asymptotic cost, it is unclear if their algorithm could ever be practical, which reduces the impact of their results. In this work, we follow their general framework, but propose an amortized bootstrapping that is conceptually simpler and asymptotically cheaper. We reduce the number of homomorphic operations per refreshed message from $O(3^\rho \cdot n^{1/\rho} \cdot \log n)$ to $O(\rho \cdot n^{1/\rho})$, and the noise overhead from $\tilde{O}(n^{2 + 3 \cdot \rho})$ to $\tilde{O}(n^{1 + \rho})$. We also make it more general, by handling non-binary messages and applying programmable bootstrapping. To obtain a concrete instantiation of our bootstrapping algorithm, we propose a double-CRT (aka RNS) version of the GSW scheme, including a new operation, called shrinking, used to speed-up homomorphic operations by reducing the dimension and ciphertext modulus of the ciphertexts. We also provide a C++ implementation of our algorithm, thus showing for the first time the practicability of the amortized bootstrapping. Moreover, it is competitive with existing bootstrapping algorithms, being even around 3.4 times faster than an equivalent non-amortized version of our bootstrapping.

The SIDH protocol is an isogeny-based key exchange protocol using supersingular isogenies, designed by Jao and De Feo in 2011. The protocol underlies the SIKE algorithm which advanced to the fourth round of NIST's post-quantum standardization project in May 2022. The algorithm was considered very promising: indeed the most significant attacks against SIDH were meet-in-the-middle variants with exponential complexity, and torsion point attacks which only applied to unbalanced parameters (and in particular, not to SIKE). This security picture dramatically changed in August 2022 with new attacks by Castryck-Decru, Maino-Martindale and Robert. Like prior attacks on unbalanced versions, these new attacks exploit torsion point information provided in the SIDH protocol. Crucially however, the new attacks embed the isogeny problem into a similar isogeny problem in a higher dimension to also affect the balanced parameters. As a result of these works, the SIKE algorithm is now fully broken both in theory and in practice. Given the considerable interest attracted by SIKE and related protocols in recent years, it is natural to seek countermeasures to the new attacks. In this paper, we introduce two such countermeasures based on partially hiding the isogeny degrees and torsion point information in the SIDH protocol. We present a preliminary analysis of the resulting schemes including non-trivial generalizations of prior attacks. Based on this analysis we suggest parameters for our M-SIDH variant with public key sizes of 4434, 7037 and 9750 bytes respectively for NIST security levels 1, 3, 5.

Private matching for compute (PMC) establishes a match between two databases owned by mutually distrusted parties ($C$ and $P$) and allows the parties to input more data for the matched records for arbitrary downstream secure computation without rerunning the private matching component. The state-of-the-art PMC protocols only support two parties and assume that both parties can participate in computationally intensive secure computation. We observe that such operational overhead limits the adoption of these protocols to solely powerful entities as small data owners or devices with minimal computing power will not be able to participate. We introduce two protocols to delegate PMC from party $P$ to untrusted cloud servers, called delegates, allowing multiple smaller $P$ parties to provide inputs containing identifiers and associated values. Our Delegated Private Matching for Compute protocols, called DPMC and D$^S$PMC, establish a join between the databases of party $C$ and multiple delegators $P$ based on multiple identifiers and compute secret shares of associated values for the identifiers that the parties have in common. We introduce a novel rerandomizable encrypted oblivious pseudorandom function (OPRF) construction, called EO, which allows two parties to encrypt, mask, and shuffle their data and is secure against semi-honest adversaries. Note that EO may be of independent interest. Our D$^S$PMC protocol limits the leakages of DPMC by combining our novel EO scheme and secure three-party shuffling. Finally, our implementation demonstrates the efficiency of our constructions by outperforming related works by approximately $10\times$ for the total protocol execution and by at least $20\times$ for the computation on the delegators.

We review the two RSA-based accumulators introduced by Camenisch and Lysyanskaya in 2002 in the setting of revocation for anonymous credential schemes, such as Idemix or BBS+. We show that in such a setting, the lower and upper bounds placed on the accumulated values in the paper are unnecessarily strict; they can be removed almost entirely (up to the group order of the credential scheme). This allows the accumulators to be used on elliptic curves of ordinary sizes, such as the ones on which BBS+ is commonly implemented. We also offer some notes and optimizations for implementations of anonymous credential schemes that use these accumulators to enable revocation.

Developers of computer-aided cryptographic tools are optimistic that formal methods will become a vital part of developing new cryptographic systems. We study the use of such tools to specify and verify the implementation of Classic McEliece, one of the code-based cryptography candidates in the fourth round of the NIST Post-Quantum standardisation Process. From our case study we draw conclusions about the practical applicability of these methods to the development of novel cryptography.

With the development of sequencing technologies, viral strain classification -- which is critical for many applications, including disease monitoring and control -- has become widely deployed. Typically, a lab (client) holds a viral sequence, and requests classification services from a centralized repository of labeled viral sequences (server). However, such ``classification as a service'' raises privacy concerns. In this paper we propose a privacy-preserving viral strain classification protocol that allows the client to obtain classification services from the server, while maintaining complete privacy of the client's viral strains. The privacy guarantee is against active servers, and the correctness guarantee is against passive ones. We implemented our protocol and performed extensive benchmarks, showing that it obtains almost perfect accuracy ($99.8\%$--$100\%$) and microAUC ($0.999$), and high efficiency (amortized per-sequence client and server runtimes of $4.95$ms and $0.53$ms, respectively, and $0.21$MB communication). In addition, we present an extension of our protocol that guarantees server privacy against passive clients, and provide an empirical evaluation showing that this extension provides the same high accuracy and microAUC, with amortized per sequences overhead of only a few milliseconds in client and server runtime, and 0.3MB in communication complexity. Along the way, we develop an enhanced packing technique in which two reals are packed in a single complex number, with support for homomorphic inner products of vectors of ciphertexts. We note that while similar packing techniques were used before, they only supported additions and multiplication by constants.

Template attacks~(TAs) are one of the most powerful Side-Channel Analysis~(SCA) attacks. The success of such attacks relies on the effectiveness of the profiling model in modeling the leakage information. A crucial step for TA is to select relevant features from the measured traces, often called Points Of Interest~(POIs), to extract the leakage information. Previous research indicates that properly selecting the input leaking features could significantly increase the attack performance. However, due to the presence of SCA countermeasures and advancements in technology nodes, such features become increasingly difficult to extract with conventional approaches such as Principle Component Analysis (PCA) and the Sum Of Squared pairwise T-differences based method (SOST). This work proposes a framework, AutoPOI, based on proximal policy optimization to automatically find, select, and scale down features. The input raw features are first grouped into small regions. The best candidates selected by the framework are further scaled down with an online-optimized dimensionality reduction neural network. Finally, the framework rewards the performance of these features with the results of TA. Based on the experimental results, the proposed framework can extract features automatically that lead to comparable state-of-the-art performance on several commonly used datasets.

Recently, in post-quantum cryptography migration, it has been shown that an IND-1-CCA-secure key encapsulation mechanisms (KEM) is required for replacing an ephemeral Diffie-Hellman (DH) in widely-used protocols, e.g., TLS, Signal, and Noise. IND-1-CCA security is a notion similar to the traditional IND-CCA security except that the adversary is restricted to one single decapsulation query. At EUROCRYPT 2022, based on CPA-secure public-key encryption (PKE), Huguenin-Dumittan and Vaudenay presented two IND-1-CCA KEM constructions called $T_{CH}$ and $T_H$, which are much more efficient than the widely-used IND-CCA-secure Fujisaki-Okamoto (FO) KEMs. The security of $T_{CH}$ was proved in both random oracle model (ROM) and quantum random oracle model (QROM). However, the QROM proof of $T_{CH}$ requires that the ciphertext size of the resulting KEM is twice as large as the one of the underlying PKE. While, the security of $T_H$ was only proved in the ROM, and the QROM proof is left open. In this paper, we present an IND-1-CCA KEM construction $T_{RH}$, which can be seen as an implicit variant $T_H$, and is as efficient as $T_H$. We prove the security of $T_{RH}$ in both ROM and QROM with much tighter reductions than Huguenin-Dumittan and Vaudenay's work. In particular, our proof will not lead to ciphertext expansion. Moreover, for $T_{RH}$, $T_H$ and $T_{CH}$, we also show that a $O(1/q)$ ($O(1/q^2)$, resp.) reduction loss is unavoidable in the ROM (QROM, resp.), and thus claim that our ROM proof is optimal in tightness. Finally, we make a comprehensive comparison among the relative strengths of IND-1-CCA and IND-CCA in the ROM and QROM.

This paper investigates different ways of applying multi-task learning in the context of two masked AES implementations (via the ASCADv1 and ASCADv2 databases). We propose novel ideas: jointly using multiple single-task models (aka multi-target learning), custom layers (enabling the use of multi-task learning without the need for information about randomness), and hierarchical multi-task models (owing to the idea of encoding the hierarchy flow directly into a multi-task learning model). Our work provides comparisons with existing approaches to deep learning and delivers a first attack using multi-task models without randomness during training, and a new best attack for the ASCADv2 dataset.

The redundant of multimedia data made an unnecessary waste in encrypted cloud storage, unlike text with completely consistent content, multimedia data allows a certain degree of similarity in deduplication, In this work, we focus on the multimedia data which takes a seriously proportion of storage in scenarios such as data outsourcing to propose secure fuzzy deduplication without the additional servers based on Convergent Encryption(CE), say the Single-server Fuzzy Deduplication (SSFD). Compared to the related fuzzy deduplication, SSFD is strong at resisting brute-force attacks caused by server-server collusion, moreover, we also put server-client collusion attacks into security solutions. Additionally, to enhance the security of data, the proposed scheme provides both protection against replay attacks and verification of label consistency and adds no extra communication such as Proof of Ownership(PoW) in interaction. We separately presented a formal security analysis and performed performance at last to prove security solutions and evaluate the experimental results, it shows SSFD provides both a reliable fuzzy images secure deduplication protocol and a computationally feasible solution.