最长公共子序列作为私有搜索

Mark A. Gondree, Payman Mohassel
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引用次数: 7

摘要

在STOC 2006和CRYPTO 2007上,Beimel等人为解决搜索问题的算法引入了一组隐私要求。本文将最长公共子序列(LCS)问题视为一个私有搜索问题,其任务是找到LCS的字符串(或相应的嵌入)。我们表明,确定性选择策略不满足私有搜索问题所考虑的隐私保证,事实上,可能会“泄露”与整个输入成比例的信息量。然后,我们提出并研究了LCS问题的几种隐私结构,并设计了新的有效的输出采样和等效保护算法,这些算法可以证明满足相应的隐私概念。在此过程中,我们还提供了有限正则语言的输出采样和等效保护算法,这可能是独立的兴趣。
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Longest common subsequence as private search
At STOC 2006 and CRYPTO 2007, Beimel et. al. introduced a set of privacy requirements for algorithms that solve search problems. In this paper, we consider the longest common subsequence (LCS) problem as a private search problem, where the task is to find a string of (or embedding corresponding to) an LCS. We show that deterministic selection strategies do not meet the privacy guarantees considered for private search problems and, in fact, may "leak" an amount of information proportional to the entire input. We then put forth and investigate several privacy structures for the LCS problem and design new and efficient output sampling and equivalence protecting algorithms that provably meet the corresponding privacy notions. Along the way, we also provide output sampling and equivalence protecting algorithms for finite regular languages, which may be of independent interest.
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