Privacy-preserving equality test towards big data

Tushar Kanti Saha, Takeshi Koshiba

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    In this paper, we review the problem of private batch equality test (PriBET) that was proposed by Saha and Koshiba (3rd APWConCSE 2016). They described this problem to find the equality of an integer within a set of integers between two parties who do not want to reveal their information if they do not equal. For this purpose, they proposed the PriBET protocol along with a packing method using the binary encoding of data. Their protocol was secured by using ring-LWE based somewhat homomorphic encryption (SwHE) in the semi-honest model. But this protocol is not fast enough to address the big data problem in some practical applications. To solve this problem, we propose a base-N fixed length encoding based PriBET protocol using SwHE in the same semi-honest model. Here we did our experiments for finding the equalities of 8–64-bit integers. Furthermore, our experiments show that our protocol is able to evaluate more than one million (resp. 862 thousand) of equality comparisons per minute for 8-bit (resp. 16-bit) integers with an encoding size of base 256 (resp. 65536). Besides, our protocol works more than 8–20 in magnitude than that of Saha and Koshiba.

    Original languageEnglish
    Title of host publicationFoundations and Practice of Security - 10th International Symposium, FPS 2017, Revised Selected Papers
    PublisherSpringer-Verlag
    Pages95-110
    Number of pages16
    ISBN (Print)9783319756493
    DOIs
    Publication statusPublished - 2018 Jan 1
    Event10th International Symposium on Foundations and Practice of Security, FPS 2017 - Nancy, France
    Duration: 2017 Oct 232017 Oct 25

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume10723 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other10th International Symposium on Foundations and Practice of Security, FPS 2017
    CountryFrance
    CityNancy
    Period17/10/2317/10/25

    Fingerprint

    Privacy Preserving
    Equality
    Cryptography
    Batch
    Homomorphic Encryption
    Encoding
    Integer
    Experiments
    Packing
    Experiment
    Big data
    Binary
    Ring
    Evaluate
    Model

    Keywords

    • Base-N encoding
    • Homomorphic encryption
    • Packing method
    • Private batch equality test

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

    Cite this

    Saha, T. K., & Koshiba, T. (2018). Privacy-preserving equality test towards big data. In Foundations and Practice of Security - 10th International Symposium, FPS 2017, Revised Selected Papers (pp. 95-110). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10723 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-319-75650-9_7

    Privacy-preserving equality test towards big data. / Saha, Tushar Kanti; Koshiba, Takeshi.

    Foundations and Practice of Security - 10th International Symposium, FPS 2017, Revised Selected Papers. Springer-Verlag, 2018. p. 95-110 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10723 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Saha, TK & Koshiba, T 2018, Privacy-preserving equality test towards big data. in Foundations and Practice of Security - 10th International Symposium, FPS 2017, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10723 LNCS, Springer-Verlag, pp. 95-110, 10th International Symposium on Foundations and Practice of Security, FPS 2017, Nancy, France, 17/10/23. https://doi.org/10.1007/978-3-319-75650-9_7
    Saha TK, Koshiba T. Privacy-preserving equality test towards big data. In Foundations and Practice of Security - 10th International Symposium, FPS 2017, Revised Selected Papers. Springer-Verlag. 2018. p. 95-110. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-75650-9_7
    Saha, Tushar Kanti ; Koshiba, Takeshi. / Privacy-preserving equality test towards big data. Foundations and Practice of Security - 10th International Symposium, FPS 2017, Revised Selected Papers. Springer-Verlag, 2018. pp. 95-110 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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