Hardware Trojan Detection Utilizing Machine Learning Approaches

Kento Hasegawa, Youhua Shi, Nozomu Togawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Citations (Scopus)

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 312018 Aug 3

Publication series

NameProceedings - 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

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
Country/TerritoryUnited States
CityNew York
Period18/7/3118/8/3

Keywords

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

ASJC Scopus subject areas

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

Fingerprint

Dive into the research topics of 'Hardware Trojan Detection Utilizing Machine Learning Approaches'. Together they form a unique fingerprint.

Cite this