Languages with Efficient Zero-Knowledge PCPs are in SZK
A Zero-Knowledge PCP (ZK-PCP) is a randomized PCP such that the view of any (perhaps cheating) efficient verifier can be efficiently simulated up to small statistical distance. Kilian, Petrank, and Tardos (STOC ’97) constructed ZK-PCPs for all languages in NEXP. Ishai, Mahmoody, and Sahai (TCC ’12), motivated by cryptographic applications, revisited the possibility of efficient ZK-PCPs for all of NP where the PCP is encoded as a polynomial-size circuit that given a query i returns the i t h symbol of the PCP. Ishai et al showed that there is no efficient ZK-PCP for NP with a non-adaptive verifier, that prepares all of its PCP queries before seeing any answers, unless NP ⊆ coAM and the polynomial-time hierarchy collapses. The question of whether adaptive verification can lead to efficient ZK-PCPs for NP remained open.
In this work, we resolve this question and show that any language or promise problem with efficient ZK-PCPs must be in SZK (the class of promise problems with a statistical zero-knowledge single prover proof system). Therefore, no NP-complete problem can have an efficient ZK-PCP unless NP ⊆ SZK (which also implies NP ⊆ coAM and the polynomial-time hierarchy collapses). We prove our result by reducing any promise problem with an efficient ZK-PCP to two instances of the Conditional Entropy Approximation problem defined and studied by Vadhan (FOCS’04) which is known to be complete for the class SZK.
KeywordsProbabilistically Checkable Proofs Statistical Zero- Knowledge
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