[Resource Topic] 2023/695: Non-Interactive Zero-Knowledge from Non-Interactive Batch Arguments

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Non-Interactive Zero-Knowledge from Non-Interactive Batch Arguments

Authors: Jeffrey Champion, David J. Wu


Zero-knowledge and succinctness are two important properties that arise in the study of non-interactive arguments. Previously, Kitagawa et al. (TCC 2020) showed how to obtain a non-interactive zero-knowledge (NIZK) argument for NP from a succinct non-interactive argument (SNARG) for NP. In particular, their work demonstrates how to leverage the succinctness property from an argument system and transform it into a zero-knowledge property.

In this work, we study a similar question of leveraging succinctness for zero-knowledge. Our starting point is a batch argument for NP, a primitive that allows a prover to convince a verifier of T NP statements x_1, \ldots, x_T with a proof whose size scales sublinearly with T. Unlike SNARGs for NP, batch arguments for NP can be built from group-based assumptions in both pairing and pairing-free groups and from lattice-based assumptions. The challenge with batch arguments is that the proof size is only amortized over the number of instances, but can still encode full information about the witness to a small number of instances.

We show how to combine a batch argument for NP with a local pseudorandom generator (i.e., a pseudorandom generator where each output bit only depends on a small number of input bits) and a dual-mode commitment scheme to obtain a NIZK for NP. Our work provides a new generic approach of realizing zero-knowledge from succinctness and highlights a new connection between succinctness and zero-knowledge.

ePrint: https://eprint.iacr.org/2023/695

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