Deep Learning on Private Data

被引：0

作者：

Riazi M.S. ^{[1
]}

Darvish Rouani B. ^{[2
]}

Koushanfar F. ^{[1
]}

机构：

[1] Electrical and Computer Engineering, University of California San Diego

来源：

IEEE Security and Privacy | 2019年 / 17卷 / 06期

关键词：

Privacy-preserving techniques;

D O I：

10.1109/MSEC.2019.2935666

中图分类号：

学科分类号：

摘要：

Emerging complex deep neural networks require vast amounts of data to achieve high precision. However, the information is often collected from user logs and personal data. In this article, we summarize recent cryptographic methodologies for provably privacy-preserving deep learning and inference. © 2003-2012 IEEE.

引用

页码：54 / 63

页数：9

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