Statistically Hiding Commitments and Statistical Zero-Knowledge Arguments from Any One-Way Function

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Statistically Hiding Commitments and Statistical Zero-Knowledge Arguments from Any One-Way Function

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Title: Statistically Hiding Commitments and Statistical Zero-Knowledge Arguments from Any One-Way Function
Author: Haitner, Iftach; Nguyen, Minh-Huyen; Ong, Shien Jin; Reingold, Omer; Vadhan, Salil P.

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Citation: Haitner, Iftach, Minh-Huyen Nguyen, Shien Jin Ong, Omer Reingold, and Salil Vadhan. 2009. “Statistically Hiding Commitments and Statistical Zero-Knowledge Arguments from Any One-Way Function.” SIAM Journal on Computing 39, no. 3: 1153–1218.
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Abstract: We give a construction of statistically hiding commitment schemes (those in which the hiding property holds against even computationally unbounded adversaries) under the minimal complexity assumption that one-way functions exist. Consequently, one-way functions suffice to give statistical zero-knowledge arguments for any NP statement (whereby even a computationally unbounded adversarial verifier learns nothing other than the fact that the assertion being proven is true, and no polynomial-time adversarial prover can convince the verifier of a false statement). These results resolve an open question posed by Naor et al.
Published Version: doi:10.1137/080725404
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:14123818
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