Making zero-knowledge provers efficient

Abstract

We look at the question of how powerful a prover must be to give a zero-knowledge proof.We present the first unconditional bounds on the complexity of a statistical ZK prover.The result is that if a language possesses a statistical zero-knowledge then it also possesses a statistical zero-knowledge proof in which the prover runs in probabilistic, polynomial time with an NP oracle.Previously this was only known given the existence of one-way permutations. Extendingthese techniques to protocols of knowledge complexity k(n) >0, we derive bounds on the time complexity of languages of "small" knowledge complexity.Underlying these results is a technique for efficiently generating an "almost" random element of a set S E P.Namely, we construct a probabilistic machine with an NP oracle which, on input 1" and 6 > 0 runs in time polynomial in n and lg 6-1, and outputs a random string from a distribution within distance 6 of the uniform distribution on S n {O, l}~.