47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06) Statistical Zero-Knowledge Arguments for NP from Any One-Way Function Berkeley, California October 21-October 24 ISBN: 0-7695-2720-5
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FOCS.2006.71
We show that every language in NP has a statistical zero-knowledge argument system under the (minimal) complexity assumption that one-way functions exist. In such protocols, even a computationally unbounded verifier cannot learn anything other than the fact that the assertion being proven is true, whereas a polynomial-time prover cannot convince the verifier to accept a false assertion except with negligible probability. This resolves an open question posed by Naor, Ostrovsky, Venkatesan, and Yung (CRYPTO ?92, J. Cryptology ?98). Departing from previous works on this problem, we do not construct standard statistically hiding commitments from any one-way function. Instead, we construct a relaxed variant of commitment schemes called "1-out-of-2-binding commitments," recently introduced by Nguyen and Vadhan (STOC ?06).
Citation:
Minh-Huyen Nguyen, Shien Jin Ong, Salil Vadhan, "Statistical Zero-Knowledge Arguments for NP from Any One-Way Function," focs, pp.3-14, 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06), 2006 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||