Designing hardware trojans and their detection based on a SVM-based approach

Tomotaka Inoue, Kento Hasegawa, Masao Yanagisawa, Nozomu Togawa

研究成果: Conference contribution

21 被引用数 (Scopus)

抄録

Since hardware production become inexpensive and international, hardware vendors often outsource their products to third-party vendors. Due to the situation, malicious vendors can easily insert malfunctions (also known as 'hardware Trojans') to their products. In this paper, we experimentally evaluate a machine-learning-based hardware-Trojan detection method using several hardware Trojans we designed. To begin with, we design three types of hardware Trojans and insert them to simple RS232 transceiver circuits. After that, we learn known netlists, where we know which nets are Trojan ones or normal ones beforehand, using a machine-learning-based hardware-Trojan detection method with a support vector machine (SVM) classifier. Finally, we classify the nets in the designed hardware-Trojan-inserted netlists into a set of Trojan nets and that of normal nets using the learned classifier. The experimental results demonstrate that the hardware-Trojan detection method with the SVM-based approach can detect a part of hardware Trojans we designed.

本文言語English
ホスト出版物のタイトルProceedings - 2017 IEEE 12th International Conference on ASIC, ASICON 2017
編集者Yajie Qin, Zhiliang Hong, Ting-Ao Tang
出版社IEEE Computer Society
ページ811-814
ページ数4
ISBN(電子版)9781509066247
DOI
出版ステータスPublished - 2017 7月 1
イベント12th IEEE International Conference on Advanced Semiconductor Integrated Circuits, ASICON 2017 - Guiyang, China
継続期間: 2017 10月 252017 10月 28

出版物シリーズ

名前Proceedings of International Conference on ASIC
2017-October
ISSN(印刷版)2162-7541
ISSN(電子版)2162-755X

Other

Other12th IEEE International Conference on Advanced Semiconductor Integrated Circuits, ASICON 2017
国/地域China
CityGuiyang
Period17/10/2517/10/28

ASJC Scopus subject areas

  • ハードウェアとアーキテクチャ
  • 電子工学および電気工学

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