Shorter Quasi-Adaptive NIZK Proofs for Linear Subspaces

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Shorter Quasi-Adaptive NIZK Proofs for Linear Subspaces
We define a novel notion of quasi-adaptive non-interactive zero knowledge (NIZK) proofs for probability distributions on parametrized languages. It is quasi-adaptive in the sense that the common reference string (CRS) generator can generate the CRS depending on the language parameters. However, the simulation is required to be uniform, i.e., a single efficient simulator should work for the whole class of parametrized languages. For distributions on languages that are linear subspaces of vector spaces over bilinear groups, we give quasi-adaptive computationally sound NIZKs that are shorter and more efficient than Groth-Sahai NIZKs. For many cryptographic applications quasi-adaptive NIZKs suffice, and our constructions can lead to significant improvements in the standard model. Our construction can be based on any k-linear assumption, and in particular under the eXternal Diffie Hellman (XDH) assumption our proofs are even competitive with Random-Oracle based Σ-protocol NIZK proofs. W...
Charanjit S. Jutla, Arnab Roy
Added 27 Apr 2014
Updated 27 Apr 2014
Type Journal
Year 2013
Authors Charanjit S. Jutla, Arnab Roy
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