Hardware Trojan Detection Utilizing Machine Learning Approaches

Kento Hasegawa, Youhua Shi, Nozomu Togawa

    研究成果

    11 被引用数 (Scopus)

    抄録

    Hardware security has become a serious concern in recent years. Due to the outsourcing in hardware production, malicious circuits (or hardware Trojans) can be easily inserted into hardware products by attackers. Since hardware Trojans are tiny and stealthy, their detection is difficult. Under the circumstances, numerous hardware-Trojan detection methods have been proposed. In this paper, we elaborate the overview of hardware-Trojan detection and review the hardware-Trojan detection methods using machine learning which is one of the state-of-the-art approaches.

    本文言語English
    ホスト出版物のタイトルProceedings - 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ1891-1896
    ページ数6
    ISBN(印刷版)9781538643877
    DOI
    出版ステータスPublished - 2018 9 5
    イベント17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018 - New York, United States
    継続期間: 2018 7 312018 8 3

    Other

    Other17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018
    国/地域United States
    CityNew York
    Period18/7/3118/8/3

    ASJC Scopus subject areas

    • コンピュータ ネットワークおよび通信
    • ハードウェアとアーキテクチャ
    • 情報システム
    • 情報システムおよび情報管理
    • 安全性、リスク、信頼性、品質管理

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