Paper 2019/406

Fine-Grained and Controlled Rewriting in Blockchains: Chameleon-Hashing Gone Attribute-Based

David Derler, Kai Samelin, Daniel Slamanig, and Christoph Striecks

Abstract

Blockchain technologies recently received a considerable amount of attention. While the initial focus was mainly on the use of blockchains in the context of cryptocurrencies such as Bitcoin, application scenarios now go far beyond this. Most blockchains have the property that once some object, e.g., a block or a transaction, has been registered to be included into the blockchain, it is persisted and there are no means to modify it again. While this is an essential feature of most blockchain scenarios, it is still often desirable - at times it may be even legally required - to allow for breaking this immutability in a controlled way. Only recently, Ateniese et al. (EuroS&P 2017) proposed an elegant solution to this problem on the block level. Thereby, the authors replace standard hash functions with so-called chameleon-hashes (Krawczyk and Rabin, NDSS 2000). While their work seems to offer a suitable solution to the problem of controlled re-writing of blockchains, their approach is too coarse-grained in that it only offers an all-or-nothing solution. We revisit this idea and introduce the novel concept of policy-based chameleonhashes (PCH). PCHs generalize the notion of chameleon-hashes by giving the party computing a hash the ability to associate access policies to the generated hashes. Anyone who possesses enough privileges to satisfy the policy can then find arbitrary collisions for a given hash. We then apply this concept to transaction-level rewriting within blockchains, and thus support fine-grained and controlled modifiability of blockchain objects. Besides modeling PCHs, we present a generic construction of PCHs (using a strengthened version of chameleon-hashes with ephemeral trapdoors which we also introduce), rigorously prove its security, and instantiate it with efficient building blocks. We report first implementation results.