Trojan-net feature extraction and its application to hardware-Trojan detection for gate-level netlists using random forest

被引：0

作者：

Hasegawa, Kento ^{[1
]}

Yanagisawa, Masao ^{[1
]}

Togawa, Nozomu ^{[1
]}

机构：

[1] Dept. of Computer Science and Communications, Engineering, Waseda University, Tokyo,169-8555, Japan

来源：

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences | 2017年 / E100A卷 / 12期

关键词：

714.2 Semiconductor Devices and Integrated Circuits - 716.1 Information Theory and Signal Processing - 723 Computer Software; Data Handling and Applications - 903.1 Information Sources and Analysis - 921.4 Combinatorial Mathematics; Includes Graph Theory; Set Theory - 961 Systems Science;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

引用

页码：2857 / 2868

共 42 条

[41] Gradual-N-Justification (GNJ) to Reduce False-Positive Hardware Trojan Detection in Gate-Level Netlist
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[42] A Feature-Adaptive and Scalable Hardware Trojan Detection Framework For Third-party IPs Utilizing Multilevel Feature Analysis and Random Forest
Liu, Yanjiang
Li, Junwei
Guo, Pengfei
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Wang, Junjie
Zhong, Jingxin
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