Neural Network-Based Side Channel Attacks and Countermeasures - 文章详情页

作者：

Serpanos, Dimitrios (Serpanos, Dimitrios.) | Yang, Shengqi (Yang, Shengqi.) | Wolf, Marilyn (Wolf, Marilyn.)

收录：

CPCI-S

摘要：

This　paper　surveys　results　in　the　use　of　neural　networks　and　deep　learning　in　two　areas　of　hardware　security:　power　attacks　and　physically-unclonable　functions　(PUFs).

关键词：

power attack deep learning machine learning physically unclonable function PUF hardware security

作者机构：

[ 1 ] [Serpanos, Dimitrios]Univ Patras, Dept ECE, Patras, Greece
[ 2 ] [Yang, Shengqi]Beijing Univ Technol, Sch Software Engn, Beijing, Peoples R China
[ 3 ] [Wolf, Marilyn]Univ Nebraska, Dept CSE, Lincoln, NE USA

通讯作者信息：

[Serpanos, Dimitrios]Univ Patras, Dept ECE, Patras, Greece

电子邮件地址：

serpanos@ece.patras.edu |
syang@bjut.edu.cn |
mwolf@unl.edu

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相关关键词：

Neural network-based side channel attacks and countermeasures
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来源：

IEEE DESIGN AUTOMATION CONFERENCE (DAC)

ISSN： 0738-100X

年份： 2020

语种：英文

被引次数：

WoS核心集被引频次： 2

SCOPUS被引频次：

ESI高被引论文在榜： 0 展开所有

万方被引频次：

中文被引频次：

近30日浏览量： 4

归属院系：

信息学部软件学院

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