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  • Privacy-enhanced machine learning with functional encryption
    Marc, Tilen ...
    Functional encryption is a generalization of public-key encryption in which possessing a secret functional key allows one to learn a function of what the ciphertext is encrypting. This paper ... introduces the first fully-fledged open source cryptographic libraries for functional encryption. It also presents how functional encryption can be used to build efficient privacy-enhanced machine learning models and it provides an implementation of three prediction services that can be applied on the encrypted data. Finally, the paper discusses the advantages and disadvantages of the alternative approach for building privacy-enhanced machine learning models by using homomorphic encryption.
    Vir: Computer Security - ESORICS 2019 : 24th European Symposium on Research in Computer Security, Luxembourg, September 23-27, 2019 : proceedings. Part 1 (Str. 3-21)
    Vrsta gradiva - prispevek na konferenci
    Leto - 2019
    Jezik - angleški
    COBISS.SI-ID - 18935897

    Povezava(-e):

    https://doi.org/10.1007/978-3-030-29959-0_1
    DOI

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