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Efficient Disjointness Tests for Private Datasets

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Information Security and Privacy (ACISP 2008)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 5107))

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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.

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Yi Mu Willy Susilo Jennifer Seberry

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Ye, Q., Wang, H., Pieprzyk, J., Zhang, XM. (2008). Efficient Disjointness Tests for Private Datasets. In: Mu, Y., Susilo, W., Seberry, J. (eds) Information Security and Privacy. ACISP 2008. Lecture Notes in Computer Science, vol 5107. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70500-0_12

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  • DOI: https://doi.org/10.1007/978-3-540-70500-0_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69971-2

  • Online ISBN: 978-3-540-70500-0

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