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Electronic Colloquium on Computational Complexity

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REPORTS > AUTHORS > PAVEL RAYKOV:
All reports by Author Pavel Raykov:

TR17-038 | 23rd February 2017
Benny Applebaum, Barak Arkis, Pavel Raykov, Prashant Nalini Vasudevan

Conditional Disclosure of Secrets: Amplification, Closure, Amortization, Lower-bounds, and Separations

Revisions: 1

In the \emph{conditional disclosure of secrets} problem (Gertner et al., J. Comput. Syst. Sci., 2000) Alice and Bob, who hold inputs $x$ and $y$ respectively, wish to release a common secret $s$ to Carol (who knows both $x$ and $y$) if only if the input $(x,y)$ satisfies some predefined predicate ... more >>>


TR16-082 | 22nd May 2016
Benny Applebaum, Pavel Raykov

Fast Pseudorandom Functions Based on Expander Graphs

We present direct constructions of pseudorandom function (PRF) families based on Goldreich's one-way function. Roughly speaking, we assume that non-trivial local mappings $f:\{0,1\}^n\rightarrow \{0,1\}^m$ whose input-output dependencies graph form an expander are hard to invert. We show that this one-wayness assumption yields PRFs with relatively low complexity. This includes weak ... more >>>


TR15-206 | 15th December 2015
Benny Applebaum, Pavel Raykov

From Private Simultaneous Messages to Zero-Information Arthur-Merlin Protocols and Back

Goos, Pitassi and Watson (ITCS, 2015) have recently introduced the notion of Zero-Information Arthur-Merlin Protocols (ZAM). In this model, which can be viewed as a private version of the standard Arthur-Merlin communication complexity game, Alice and Bob are holding a pair of inputs $x$ and $y$ respectively, and Merlin, the ... more >>>


TR15-186 | 24th November 2015
Benny Applebaum, Pavel Raykov

On the Relationship between Statistical Zero-Knowledge and Statistical Randomized Encodings

\emph{Statistical Zero-knowledge proofs} (Goldwasser, Micali and Rackoff, SICOMP 1989) allow a computationally-unbounded server to convince a computationally-limited client that an input $x$ is in a language $\Pi$ without revealing any additional information about $x$ that the client cannot compute by herself. \emph{Randomized encoding} (RE) of functions (Ishai and Kushilevitz, FOCS ... more >>>




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