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Can You Find The One for Me?

Published:15 January 2018Publication History

ABSTRACT

Private set-intersection (PSI) allows a client to only learn the intersection between his/her set C and the set S of another party, while this latter party learns nothing. We aim to enhance PSI in different dimensions, motivated by the use cases of increasingly popular online matchmaking --- Meeting "the one'' who possesses all desired qualities and free from any undesirable attributes may be a bit idealistic. In this paper, we realize over- (resp. below-) threshold PSI, such that the client learns the intersection (or other auxiliary private data) only when $|C \cap S| > t$ (resp. $łeq t$). The threshold corresponds to tunable criteria for (mis)matching, without marking all possible attributes as desired or not. In other words, the matching criteria are in a succinct form and the matching computation does not exhaust the whole universe of attributes. To the best of our knowledge, our constructions are the very first solution for these two open problems posed by Bradley etal. (SCN '16) and Zhao and Chow (PoPETS '17), without resorting to the asymptotically less efficient generic approach from garbled circuits. Moreover, we consider an "outsourced'' setting with a service provider coordinating the PSI execution, instead of having two strangers to be online simultaneously for running a highly-interactive PSI directly with each other. Outsourcing our protocols are arguably optimal --- the two users perform O(|C|) and O(1) decryptions, for unlocking the private set C and the outcome of matching.

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          • Published in

            cover image ACM Conferences
            WPES'18: Proceedings of the 2018 Workshop on Privacy in the Electronic Society
            October 2018
            190 pages
            ISBN:9781450359894
            DOI:10.1145/3267323

            Copyright © 2018 ACM

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            Publication History

            • Published: 15 January 2018

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            WPES'18 Paper Acceptance Rate11of25submissions,44%Overall Acceptance Rate106of355submissions,30%

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