Efficient robust private set intersection

Authors:
Dana Dachman-Soled;Tal Malkin;Mariana Raykova;Moti Yung
Affiliations:
Microsoft Research New England, 1 Memorial Drive, Cambridge, MA 02142, USA.;Columbia University, 1214 Amsterdam Avenue, New York, New York 10027, USA.;Columbia University, 1214 Amsterdam Avenue, New York, New York 10027, USA.;Google Inc. and Columbia University, 1214 Amsterdam Avenue, New York, New York 10027, USA
Venue:
International Journal of Applied Cryptography
Year:
2012

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Abstract

Computing set intersection privately and efficiently between two mutually mistrusting parties is an important basic procedure in the area of private data mining. Assuring robustness, namely, coping with potentially arbitrarily misbehaving (i.e., malicious) parties, while retaining protocol efficiency (rather than employing costly generic techniques) is an open problem. In this work, the first solution to this problem is presented.