Side-Channel Hybrid Attacks on Strong Physical Unclonable Function

被引：0

作者：

Liu W. ^{[1
]}

Jiang L.-H. ^{[1
]}

Chang R. ^{[1
]}

机构：

[1] Institute of Cyberspace Security, Information Engineering University of Strategic Support Force, Zhengzhou, 450002, Henan

来源：

Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2019年 / 47卷 / 12期

关键词：

Fault injection; Machine learning; Power analysis; Reliability; Side-channel hybrid attack; Strong PUF;

D O I：

10.3969/j.issn.0372-2112.2019.12.025

中图分类号：

学科分类号：

摘要：

Due to the tamperproof and lightweight nature, physical unclonable function are proposed to provide security with low cost for the internet of things.Security of PUF itself has attracted much more attention.Almost all strong PUF can be modeled using machine learning techniques, while the complicated PUF with non-linear structure, which are resistant to machine learning modeling, are vulnerable to side channel attacks.According to the unified symbol rules, the paper presents existing side channel attack methods on strong PUFs, such as reliability analysis, power analysis and fault injection.The principles, performance and applications of side channel/machine learning hybrid attack methods are elaborated and analyzed.In the end, the temporary predicaments and countermeasures of side channel attack on PUF are discussed. © 2019, Chinese Institute of Electronics. All right reserved.

引用

页码：2639 / 2646

页数：7

共 41 条

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