CCCRJul 30, 2016

Improved Non-Malleable Extractors, Non-Malleable Codes and Independent Source Extractors

arXiv:1608.00127v1117 citations
Originality Incremental advance
AI Analysis

This work addresses foundational issues in cryptography for secure communication and data integrity, offering incremental but substantial advances over prior methods.

The paper tackles problems in randomness extraction and tamper-resilient cryptography by providing improved constructions for non-malleable extractors, codes, and independent source extractors, resulting in exponential improvements in rates and optimal parameters such as seed length and entropy loss.

In this paper we give improved constructions of several central objects in the literature of randomness extraction and tamper-resilient cryptography. Our main results are: (1) An explicit seeded non-malleable extractor with error $ε$ and seed length $d=O(\log n)+O(\log(1/ε)\log \log (1/ε))$, that supports min-entropy $k=Ω(d)$ and outputs $Ω(k)$ bits. Combined with the protocol in \cite{DW09}, this gives a two round privacy amplification protocol with optimal entropy loss in the presence of an active adversary, for all security parameters up to $Ω(k/\log k)$. (2) An explicit non-malleable two-source extractor for min-entropy $k \geq (1-γ)n$, some constant $γ>0$, that outputs $Ω(k)$ bits with error $2^{-Ω(n/\log n)}$. Combined with the connection in \cite{CG14b} this gives a non-malleable code in the two-split-state model with relative rate $Ω(1/\log n)$. This exponentially improves previous constructions, all of which only achieve rate $n^{-Ω(1)}$.\footnote{The work of Aggarwal et. al \cite{ADKO15} had a construction which "achieves" constant rate, but recently the author found an error in their proof.} (3)A two-source extractor for min-entropy $O(\log n \log \log n)$, which also implies a $K$-Ramsey graph on $N$ vertices with $K=(\log N)^{O(\log \log \log N)}$. We also obtain a seeded non-malleable $9$-source extractor with optimal seed length, which in turn gives a $10$-source extractor for min-entropy $O(\log n)$. Previously the best known extractor for such min-entropy requires $O(\log \log n)$ sources \cite{CohL16}. Independent of our work, Cohen \cite{Cohen16} obtained similar results to (1) and the two-source extractor, except the dependence on $ε$ is $\log(1/ε)(\log \log (1/ε))^{O(1)}$ and the two-source extractor requires min-entropy $\log n (\log \log n)^{O(1)}$.

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