Hardware Trojan Detection Utilizing Machine Learning Approaches

Kento Hasegawa, Youhua Shi, Nozomu Togawa

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    Abstract

    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.

    Original languageEnglish
    Title of host publicationProceedings - 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
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1891-1896
    Number of pages6
    ISBN (Print)9781538643877
    DOIs
    Publication statusPublished - 2018 Sep 5
    Event17th 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
    Duration: 2018 Jul 31 → 2018 Aug 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
    CountryUnited States
    CityNew York
    Period18/7/31 → 18/8/3

    Keywords

    • design time
    • hardware security
    • hardware Trojan
    • IoT
    • machine learning

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Hardware and Architecture
    • Information Systems
    • Information Systems and Management
    • Safety, Risk, Reliability and Quality

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    • Cite this

    Hasegawa, K., Shi, Y., & Togawa, N. (2018). Hardware Trojan Detection Utilizing Machine Learning Approaches. In 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 (pp. 1891-1896). [8456155] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TrustCom/BigDataSE.2018.00287