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Electronic Colloquium on Computational Complexity

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REPORTS > AUTHORS > PRASHANT NALINI VASUDEVAN:
All reports by Author Prashant Nalini Vasudevan:

TR18-208 | 27th November 2018
Benny Applebaum, Prashant Nalini Vasudevan

Placing Conditional Disclosure of Secrets in the Communication Complexity Universe

In the *Conditional Disclosure of Secrets* (CDS) problem (Gertner et al., J. Comput. Syst. Sci., 2000) Alice and Bob, who hold $n$-bit inputs $x$ and $y$ respectively, wish to release a common secret $z$ to Carol (who knows both $x$ and $y$) if and only if the input $(x,y)$ satisfies ... more >>>


TR18-085 | 26th April 2018
Andrej Bogdanov, Manuel Sabin, Prashant Nalini Vasudevan

XOR Codes and Sparse Random Linear Equations with Noise

A $k$-LIN instance is a system of $m$ equations over $n$ variables of the form $s_{i[1]} + \dots + s_{i[k]} =$ 0 or 1 modulo 2 (each involving $k$ variables). We consider two distributions on instances in which the variables are chosen independently and uniformly but the right-hand sides are ... more >>>


TR17-172 | 3rd November 2017
Itay Berman, Akshay Degwekar, Ron Rothblum, Prashant Nalini Vasudevan

From Laconic Zero-Knowledge to Public-Key Cryptography

Since its inception, public-key encryption (PKE) has been one of the main cornerstones of cryptography. A central goal in cryptographic research is to understand the foundations of public-key encryption and in particular, base its existence on a natural and generic complexity-theoretic assumption. An intriguing candidate for such an assumption is ... more >>>


TR17-097 | 31st May 2017
Itay Berman, Akshay Degwekar, Ron Rothblum, Prashant Nalini Vasudevan

Multi Collision Resistant Hash Functions and their Applications

Revisions: 1

Collision resistant hash functions are functions that shrink their input, but for which it is computationally infeasible to find a collision, namely two strings that hash to the same value (although collisions are abundant).

In this work we study multi-collision resistant hash functions (MCRH) a natural relaxation of collision resistant ... more >>>


TR17-039 | 28th February 2017
Marshall Ball, Alon Rosen, Manuel Sabin, Prashant Nalini Vasudevan

Average-Case Fine-Grained Hardness

We present functions that can be computed in some fixed polynomial time but are hard on average for any algorithm that runs in slightly smaller time, assuming widely-conjectured worst-case hardness for problems from the study of fine-grained complexity. Unconditional constructions of such functions are known from before (Goldmann et al., ... more >>>


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 >>>


TR16-140 | 9th September 2016
Adam Bouland, Lijie Chen, Dhiraj Holden, Justin Thaler, Prashant Nalini Vasudevan

On SZK and PP

Revisions: 3

In both query and communication complexity, we give separations between the class NISZK, containing those problems with non-interactive statistical zero knowledge proof systems, and the class UPP, containing those problems with randomized algorithms with unbounded error. These results significantly improve on earlier query separations of Vereschagin [Ver95] and Aaronson [Aar12] ... more >>>




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