Survey: Hardware Trojan Detection for Netlist

Yipei Yang, Jing Ye, Yuan Cao, Jiliang Zhang, Xiaowei Li, Huawei Li, Yu Hu
{"title":"Survey: Hardware Trojan Detection for Netlist","authors":"Yipei Yang, Jing Ye, Yuan Cao, Jiliang Zhang, Xiaowei Li, Huawei Li, Yu Hu","doi":"10.1109/ATS49688.2020.9301614","DOIUrl":null,"url":null,"abstract":"The development of integrated circuit technology is accompanied by potential threats. Malicious modifications to circuits, known as hardware Trojans, are major security concerns. This paper gives a survey of hardware Trojan detection methods towards gate-level netlists. The detection methods are divided into search-based, threshold-based, and machine learning-based ones. This paper compares and analyzes existing works from aspects of feature selection, data balancing techniques, classification criterion, detection range. The experimental results are also selected for comparison.","PeriodicalId":220508,"journal":{"name":"2020 IEEE 29th Asian Test Symposium (ATS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 29th Asian Test Symposium (ATS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATS49688.2020.9301614","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

The development of integrated circuit technology is accompanied by potential threats. Malicious modifications to circuits, known as hardware Trojans, are major security concerns. This paper gives a survey of hardware Trojan detection methods towards gate-level netlists. The detection methods are divided into search-based, threshold-based, and machine learning-based ones. This paper compares and analyzes existing works from aspects of feature selection, data balancing techniques, classification criterion, detection range. The experimental results are also selected for comparison.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
调查:硬件木马检测的网表
集成电路技术的发展伴随着潜在的威胁。恶意修改电路,被称为硬件木马,是主要的安全问题。本文综述了针对门级网络列表的硬件木马检测方法。检测方法分为基于搜索的、基于阈值的和基于机器学习的。本文从特征选择、数据平衡技术、分类标准、检测范围等方面对已有研究成果进行了比较和分析。并选取实验结果进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
[Copyright notice] Unexpected Error Explosion in NAND Flash Memory: Observations and Prediction Scheme C-Testing of AI Accelerators * Power Supply Noise-Aware Scan Test Pattern Reshaping for At-Speed Delay Fault Testing of Monolithic 3D ICs * LBIST-PUF: An LBIST Scheme Towards Efficient Challenge-Response Pairs Collection and Machine-Learning Attack Tolerance Improvement
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1