Fast and space-efficient secure frequent pattern mining by FHE

Hiroki Imabayashi, Yu Ishimaki, Akira Umayabara, Hayato Yamana

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

    4 Citations (Scopus)

    Abstract

    In the big data era, security and privacy concerns are growing. One of the big challenges is secure Frequent Pattern Mining (FPM) over Fully Homomorphic Encryption (FHE). There exist some research efforts aimed at speeding-up, however, we have a big room so as to decrease time and space complexity. Apriori over FHE, in particular, generates a large number of ciphertexts during the support calculation, which results in both large time and space complexity. To solve it, we proposed a speedup technique, around 430 times faster and 18.9 times smaller memory usage than the state-of-the-art method, by adopting both packing and caching mechanism. In this paper, we further propose to decrease the memory space used for caching. Our goal is to discard redundant cached ciphertexts without increasing the execution time. Our experimental results show that our method decreases the memory usage by 6.09% at most in comparison with our previous method without increasing the execution time.

    Original languageEnglish
    Title of host publicationProceedings - 2016 IEEE International Conference on Big Data, Big Data 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages3983-3985
    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

    Fingerprint

    Cryptography
    Data storage equipment
    Data privacy
    Security of data
    Big data

    Keywords

    • Cache Pruning
    • Ciphertext Caching
    • Frequent Pattern Mining
    • Fully Homomorphic Encryption

    ASJC Scopus subject areas

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

    Cite this

    Imabayashi, H., Ishimaki, Y., Umayabara, A., & Yamana, H. (2017). Fast and space-efficient secure frequent pattern mining by FHE. In Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016 (pp. 3983-3985). [7841083] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2016.7841083

    Fast and space-efficient secure frequent pattern mining by FHE. / Imabayashi, Hiroki; Ishimaki, Yu; Umayabara, Akira; Yamana, Hayato.

    Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 3983-3985 7841083.

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

    Imabayashi, H, Ishimaki, Y, Umayabara, A & Yamana, H 2017, Fast and space-efficient secure frequent pattern mining by FHE. in Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016., 7841083, Institute of Electrical and Electronics Engineers Inc., pp. 3983-3985, 4th IEEE International Conference on Big Data, Big Data 2016, Washington, United States, 16/12/5. https://doi.org/10.1109/BigData.2016.7841083
    Imabayashi H, Ishimaki Y, Umayabara A, Yamana H. Fast and space-efficient secure frequent pattern mining by FHE. In Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 3983-3985. 7841083 https://doi.org/10.1109/BigData.2016.7841083
    Imabayashi, Hiroki ; Ishimaki, Yu ; Umayabara, Akira ; Yamana, Hayato. / Fast and space-efficient secure frequent pattern mining by FHE. Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 3983-3985
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