Private Substring Search on Homomorphically Encrypted Data

Yu Ishimaki, Hiroki Imabayashi, Hayato Yamana

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

    4 Citations (Scopus)

    Abstract

    With the rapid development of cloud storage services and IoT environment, how to securely and efficiently search without compromising privacy has been an indispensable problem. In order to address such a problem, much works have been proposed for searching over encrypted data. Motivated by storing sensitive data such as genomic and medical data, substring search for encrypted data has been studied. Previous work either leaks query access pattern using vulnerable cryptographic model or performs search over plaintext data by an encrypted query. Thus they are not compatible with outsourcing scenario where searched data is stored in encrypted form which is searched by an encrypted substring query without leaking query access pattern, i.e., private substring search. In order to perform private substring search, Fully Homomorphic Encryption (FHE) can be adopted although it induces computationally huge overhead. Because of the huge overhead, performing private substring search efficiently over FHE is a challenging task. In this work, we propose a private substring search protocol over encrypted data by adopting FHE followed by examining its feasibility. In particular, we make use of batching technique which can accelerate homomorphic computation in SIMD manner. In addition, we propose a data structure which can be useful to specific searching function for batched computation. Our experimental result showed our proposed method is feasible.

    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781509065172
    DOIs
    Publication statusPublished - 2017 Jun 12
    Event2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017 - Hong Kong, China
    Duration: 2017 May 292017 May 31

    Other

    Other2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017
    CountryChina
    CityHong Kong
    Period17/5/2917/5/31

    Fingerprint

    Cryptography
    Outsourcing
    Data structures
    Network protocols
    Internet of things

    Keywords

    • Burrows Wheeler Transform (BWT)
    • Fully Homomorphic Encryption (FHE)
    • Substring Search

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Networks and Communications
    • Computer Science Applications

    Cite this

    Ishimaki, Y., Imabayashi, H., & Yamana, H. (2017). Private Substring Search on Homomorphically Encrypted Data. In 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017 [7947038] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMARTCOMP.2017.7947038

    Private Substring Search on Homomorphically Encrypted Data. / Ishimaki, Yu; Imabayashi, Hiroki; Yamana, Hayato.

    2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 7947038.

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

    Ishimaki, Y, Imabayashi, H & Yamana, H 2017, Private Substring Search on Homomorphically Encrypted Data. in 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017., 7947038, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017, Hong Kong, China, 17/5/29. https://doi.org/10.1109/SMARTCOMP.2017.7947038
    Ishimaki Y, Imabayashi H, Yamana H. Private Substring Search on Homomorphically Encrypted Data. In 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 7947038 https://doi.org/10.1109/SMARTCOMP.2017.7947038
    Ishimaki, Yu ; Imabayashi, Hiroki ; Yamana, Hayato. / Private Substring Search on Homomorphically Encrypted Data. 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017. Institute of Electrical and Electronics Engineers Inc., 2017.
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