Title
Resettable statistical zero knowledge
Abstract
Two central notions of Zero Knowledge that provide strong, yet seemingly incomparable security guarantees against malicious verifiers are those of Statistical Zero Knowledge and Resettable Zero Knowledge. The current state of the art includes several feasibility and impossibility results regarding these two notions separately. However, the question of achieving Resettable Statistical Zero Knowledge (i.e., Resettable Zero Knowledge and Statistical Zero Knowledge simultaneously) for non-trivial languages remained open. In this paper, we show: — Resettable Statistical Zero Knowledge with unbounded prover: under the assumption that sub-exponentially hard one-way functions exist, rSƵK = SƵK. In other words, every language that admits a Statistical Zero-Knowledge (SƵK) proof system also admits a Resettable Statistical Zero-Knowledge (rSƵK) proof system. (Further, the result can be re-stated unconditionally provided there exists a sub-exponentially hard language in SƵK). Moreover, under the assumption that (standard) one-way functions exist, all languages L such that the complement of L is random self reducible, admit a rSƵK; in other words: co-RSR ⊆ rSƵK. — Resettable Statistical Zero Knowledge with efficient prover: efficient-prover Resettable Statistical Zero-Knowledge proof systems exist for all languages that admit hash proof systems (e.g., QNR, QR, ƊƊH, DCR). Furthermore, for these languages we construct a two-round resettable statistical witness-indistinguishable argument system. The round complexity of our proof systems is Õ(log κ), where κ is the security parameter, and all our simulators are black-box.
Year
DOI
Venue
2012
10.1007/978-3-642-28914-9_28
IACR Cryptology ePrint Archive
Keywords
DocType
Volume
zero knowledge,efficient-prover resettable statistical zero-knowledge,resettable statistical zero knowledge,hash proof system,resettable statistical zero-knowledge,statistical zero-knowledge,statistical zero knowledge,proof system,languages l,resettable zero knowledge
Conference
2011
ISSN
Citations 
PageRank 
0302-9743
5
0.47
References 
Authors
45
4
Name
Order
Citations
PageRank
Sanjam Garg1171069.92
Rafail Ostrovsky28743588.15
Ivan Visconti361240.30
Akshay Wadia41396.78