Privacy-preserving string search for genome sequences with FHE bootstrapping optimization

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

    7 Citations (Scopus)

    Abstract

    Privacy-preserving string search is a crucial task for analyzing genomics-driven big data. In this work, we propose a cryptographic protocol that uses Fully Homomorphic Encryption (FHE) to enable a client to search on a genome sequence database without leaking his/her query to the server. Though FHE supports both addition and multiplication over encrypted data, random noise inside ciphertexts grows with every arithmetic operation especially multiplication, which results in incorrect decryption when the noise amount exceeds its threshold called level. There are two approaches to avoid the incorrect decryption: one is setting the sufficient level that assures correct decryption within the limited number of operations, and the other is resetting the noise by the method called bootstrapping. It is important to find an optimal balance between overhead caused by the level and overhead caused by the bootstrapping, since using higher level deteriorates the performance of all the arithmetic operations, while the more number of bootstrappings causes more expensive overhead. In this study, we propose an efficient approach to minimize the number of bootstrappings while reducing the level as much as possible. Our experimental result shows that it runs at most 10 times faster than a naïve approach.

    Original languageEnglish
    Title of host publicationProceedings - 2016 IEEE International Conference on Big Data, Big Data 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages3989-3991
    Number of pages3
    ISBN (Electronic)9781467390040
    DOIs
    Publication statusPublished - 2017 Feb 2
    Event4th IEEE International Conference on Big Data, Big Data 2016 - Washington, United States
    Duration: 2016 Dec 52016 Dec 8

    Other

    Other4th IEEE International Conference on Big Data, Big Data 2016
    CountryUnited States
    CityWashington
    Period16/12/516/12/8

    Keywords

    • Bootstrapping
    • Fully Homomorphic Encryption (FHE)
    • Genome Sequence
    • PBWT
    • String Search

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Information Systems
    • Hardware and Architecture

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  • Cite this

    Ishimaki, Y., Imabayashi, H., Shimizu, K., & Yamana, H. (2017). Privacy-preserving string search for genome sequences with FHE bootstrapping optimization. In Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016 (pp. 3989-3991). [7841085] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2016.7841085