Efficient Disjointness Tests for Private Datasets

  • Authors:
  • Qingsong Ye;Huaxiong Wang;Josef Pieprzyk;Xian-Mo Zhang

  • Affiliations:
  • Centre for Advanced Computing --- Algorithms and Cryptography Department of Computing, Macquarie University, Australia NSW 2109;Centre for Advanced Computing --- Algorithms and Cryptography Department of Computing, Macquarie University, Australia NSW 2109 and Division of Mathematical Sciences School of Physical and Mathema ...;Centre for Advanced Computing --- Algorithms and Cryptography Department of Computing, Macquarie University, Australia NSW 2109;Centre for Advanced Computing --- Algorithms and Cryptography Department of Computing, Macquarie University, Australia NSW 2109

  • Venue:
  • ACISP '08 Proceedings of the 13th Australasian conference on Information Security and Privacy
  • Year:
  • 2008

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Abstract

We present efficient protocols for private set disjointness tests. We start from an intuition of our protocols that applies Sylvester matrices. Unfortunately, this simple construction is insecure as it reveals information about the cardinality of the intersection. More specifically, it discloses its lower bound. By using the Lagrange interpolation we provide a protocol for the honest-but-curious case without revealing any additional information. Finally, we describe a protocol that is secure against malicious adversaries. The protocol applies a verification test to detect misbehaving participants. Both protocols require O(1) rounds of communication. Our protocols are more efficient than the previous protocols in terms of communication and computation overhead. Unlike previous protocols whose security relies on computational assumptions, our protocols provide information theoretic security. To our knowledge, our protocols are first ones that have been designed without a generic secure function evaluation. More importantly, they are the most efficient protocols for private disjointness tests for the malicious adversary case.