International Association for Cryptologic Research

International Association
for Cryptologic Research


Alex Davidson


Round-optimal Verifiable Oblivious Pseudorandom Functions from Ideal Lattices 📺
Verifiable Oblivious Pseudorandom Functions (VOPRFs) are protocols that allow a client to learn verifiable pseudorandom function (PRF) evaluations on inputs of their choice. The PRF evaluations are computed by a server using their own secret key. The security of the protocol prevents both the server from learning anything about the client's input, and likewise the client from learning anything about the server's key. VOPRFs have many applications including password-based authentication, secret-sharing, anonymous authentication and efficient private set intersection. In this work, we construct the first round-optimal (online) VOPRF protocol that retains security from well-known subexponential lattice hardness assumptions. Our protocol requires constructions of non-interactive zero-knowledge arguments of knowledge (NIZKAoK). Using recent developments in the area of post-quantum zero-knowledge arguments of knowledge, we show that our VOPRF may be securely instantiated in the quantum random oracle model. We construct such arguments as extensions of prior work in the area of lattice-based zero-knowledge proof systems.
Adaptively Secure Constrained Pseudorandom Functions in the Standard Model 📺
Constrained pseudorandom functions (CPRFs) allow learning "constrained" PRF keys that can evaluate the PRF on a subset of the input space, or based on some predicate. First introduced by Boneh and Waters [AC’13], Kiayias et al. [CCS’13] and Boyle et al. [PKC’14], they have shown to be a useful cryptographic primitive with many applications. These applications often require CPRFs to be adaptively secure, which allows the adversary to learn PRF values and constrained keys in an arbitrary order. However, there is no known construction of adaptively secure CPRFs based on a standard assumption in the standard model for any non-trivial class of predicates. Moreover, even if we rely on strong tools such as indistinguishability obfuscation (IO), the state-of-the-art construction of adaptively secure CPRFs in the standard model only supports the limited class of NC1 predicates. In this work, we develop new adaptively secure CPRFs for various predicates from different types of assumptions in the standard model. Our results are summarized below. - We construct adaptively secure and O(1)-collusion-resistant CPRFs for t-conjunctive normal form (t-CNF) predicates from one-way functions (OWFs) where t is a constant. Here, O(1)-collusion-resistance means that we can allow the adversary to obtain a constant number of constrained keys. Note that t-CNF includes bit-fixing predicates as a special case. - We construct adaptively secure and single-key CPRFs for inner-product predicates from the learning with errors (LWE) assumption. Here, single-key means that we only allow the adversary to learn one constrained key. Note that inner-product predicates include t-CNF predicates for a constant t as a special case. Thus, this construction supports a more expressive class of predicates than that supported by the first construction though it loses the collusion-resistance and relies on a stronger assumption. - We construct adaptively secure and O(1)-collusion-resistant CPRFs for all circuits from the LWE assumption and indistinguishability obfuscation (IO). The first and second constructions are the first CPRFs for any non-trivial predicates to achieve adaptive security outside of the random oracle model or relying on strong cryptographic assumptions. Moreover, the first construction is also the first to achieve any notion of collusion-resistance in this setting. Besides, we prove that the first and second constructions satisfy weak 1-key privacy, which roughly means that a constrained key does not reveal the corresponding constraint. The third construction is an improvement over previous adaptively secure CPRFs for less expressive predicates based on IO in the standard model.