Fully Homomorphic Encryption for Classification in Machine Learning

被引：0
|
作者：
Arita, Seiko [1 ]
Nakasato, Shota [1 ]
机构：
[1] Inst Informat Secur, Grad Sch Informat Secur, Yokohama, Kanagawa, Japan
来源：
2017 IEEE INTERNATIONAL CONFERENCE ON SMART COMPUTING (SMARTCOMP) | 2017年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Using fully homomorphic encryption scheme, we construct fully homomorphic encryption scheme FHE4GT that can homomorphically compute an encryption of the greater-than bit that indicates x > x' or not, given two ciphertexts c and c' of x and x', respectively, without knowing the secret key. Then, we construct homomorphic classifier homClassify that can homomorphically classify a given encrypted data without decrypting it, using machine learned parameters.
引用
收藏
页码：435 / 438
页数：4
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