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A Scalable Multiparty Private Set Intersection

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Network and System Security (NSS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9408))

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Abstract

Both scalability and flexibility become crucial for privacy preserving protocols in the age of Big Data. Private Set Intersection (PSI) is one of important privacy preserving protocols. Usually, PSI is executed by 2-parties, a client and a server, where both a client and a server compute jointly the intersection of their private sets and at the end only the client learns the intersection and the server learns nothing. From the scalable point of view, however, the number of parties are not limited to two. In this paper, we propose a scalable and flexible multiparty PSI (MPSI) for the first time: the data size of each party is independent to each other and the computational complexity is independent to the number of parties. We also propose d-and-over MPSI for the first time.

This study is partly supported by Grant-in-Aid for Scientific Research (C) i15K00183) and (15K00189).

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Author information

Authors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Atsuko Miyaji & Shohei Nishida

  2. Japan Science and Technology Agency (JST) CREST, Tokyo, Japan

    Atsuko Miyaji

  3. Graduate School of Engineering, Osaka University, Suita, Japan

    Atsuko Miyaji

Authors
  1. Atsuko Miyaji
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  2. Shohei Nishida
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Corresponding author

Correspondence to Atsuko Miyaji .

Editor information

Editors and Affiliations

  1. Apt. 2A, NEW YORK, New York, USA

    Meikang Qiu

  2. University of Texas, San Antonio, Texas, USA

    Shouhuai Xu

  3. Dept. of Computer Science, Columbia University, New York, New York, USA

    Moti Yung

  4. University of Otago, Dunedin, New Zealand

    Haibo Zhang

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© 2015 Springer International Publishing Switzerland

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Miyaji, A., Nishida, S. (2015). A Scalable Multiparty Private Set Intersection. In: Qiu, M., Xu, S., Yung, M., Zhang, H. (eds) Network and System Security. NSS 2015. Lecture Notes in Computer Science(), vol 9408. Springer, Cham. https://doi.org/10.1007/978-3-319-25645-0_26

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  • DOI: https://doi.org/10.1007/978-3-319-25645-0_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25644-3

  • Online ISBN: 978-3-319-25645-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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