Secure computation of the kth-Ranked element

Gagan Aggarwal, Nina Mishra, Benny Pinkas

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

99 Scopus citations

Abstract

Given two or more parties possessing large, confidential datasets, we consider the problem of securely computing the kth-ranked element of the union of the datasets, e.g. the median of the values in the datasets. We investigate protocols with sublinear computation and communication costs. In the two-party case, we show that the kth-ranked element can be computed in log k rounds, where the computation and communication costs of each round are O(log M), where log M is the number of bits needed to describe each element of the input data. The protocol can be made secure against a malicious adversary, and can hide the sizes of the original datasets. In the multi-party setting, we show that the kth-ranked element can be computed in log M rounds, with O(s log M) overhead per round, where s is the number of parties. The multi-party protocol can be used in the two-party case and can also be made secure against a malicious adversary.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsChristian Cachin, Jan Camenisch
PublisherSpringer Verlag
Pages40-55
Number of pages16
ISBN (Print)3540219358, 9783540219354
DOIs
StatePublished - 2004
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3027
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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