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Privacy preserving data mining via homomorphic encryption


開催時期 2017-05-26 15:00~2017-05-26 16:00

場所 九州大学 伊都キャンパス ウエスト1号館 中セミナー室 W1-C-716

受講対象  

講師 Takuya Hayashi (Kobe Univ./NICT)

Abstract:
Privacy preserving data mining (PPDM) is crucially important technology for balancing the data privacy and the data utility. One strategy for realizing the PPDM is utilizing homomorphic encryption (HE), which enables us to compute some operations on encrypted data. However, current HEs have several issues, e.g., large computational resource requirement and limitation of computable operations. In this talk, firstly we will introduce our results of HE: security updatable homomorphic encryption and efficient secure inner product computation, then introduce how to utilize HE to compute logistic regression efficiently and securely.
This is a joint work with my colleagues at NICT: Yoshinori Aono, Le Trieu Phong, and Lihua Wang.