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The (True) Complexity of Statistical Zero Knowledge (Extended Abstract)
 Proceedings of the 22nd Annual ACM Symposium on the Theory of Computing, ACM
, 1990
"... ) Mihir Bellare Silvio Micali y Rafail Ostrovsky z MIT Laboratory for Computer Science 545 Technology Square Cambridge, MA 02139 Abstract Statistical zeroknowledge is a very strong privacy constraint which is not dependent on computational limitations. In this paper we show that given a comp ..."
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) Mihir Bellare Silvio Micali y Rafail Ostrovsky z MIT Laboratory for Computer Science 545 Technology Square Cambridge, MA 02139 Abstract Statistical zeroknowledge is a very strong privacy constraint which is not dependent on computational limitations. In this paper we show that given a complexity assumption a much weaker condition suffices to attain statistical zeroknowledge. As a result we are able to simplify statistical zeroknowledge and to better characterize, on many counts, the class of languages that possess statistical zeroknowledge proofs. 1 Introduction An interactive proof involves two parties, a prover and a verifier, who talk back and forth. The prover, who is computationally unbounded, tries to convince the probabilistic polynomial time verifier that a given theorem is true. A zeroknowledge proof is an interactive proof with an additional privacy constraint: the verifier does not learn why the theorem is true [11]. That is, whatever the polynomialtime verif...