Designing subspecies of hardware trojans and their detection using neural network approach

Tomotaka Inoue, Kento Hasegawa, Yuki Kobayashi, Masao Yanagisawa, Nozomu Togawa

研究成果: Conference contribution

5 被引用数 (Scopus)

抄録

Due to the recent technological development, home appliances and electric devices are equipped with high-performance hardware device. Since demand of hardware devices is increased, production base become internationalized to mass-produce hardware devices with low cost and hardware vendors outsource their products to third-party vendors. Accordingly, malicious third-party vendors can easily insert malfunctions (also known as 'hardware Trojans') into their products. In this paper, we design six kinds of hardware Trojans at a gate-level netlist, and apply a neural-network (NN) based hardware-Trojan detection method to them. The designed hardware Trojans are different in trigger circuits. In addition, we insert them to normal circuits, and detect hardware Trojans using a machine-learning-based hardware-Trojan detection method with neural networks. In our experiment, we learned Trojan-infected benchmarks using NN, and performed cross validation to evaluate the learned NN. The experimental results demonstrate that the average TPR (True Positive Rate) becomes 72.9%, the average TNR (True Negative Rate) becomes 90.0%.

本文言語English
ホスト出版物のタイトル2018 IEEE 8th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018
出版社IEEE Computer Society
ISBN(電子版)9781538660959
DOI
出版ステータスPublished - 2018 12 13
イベント8th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018 - Berlin, Germany
継続期間: 2018 9 22018 9 5

出版物シリーズ

名前IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
2018-September
ISSN(印刷版)2166-6814
ISSN(電子版)2166-6822

Other

Other8th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018
国/地域Germany
CityBerlin
Period18/9/218/9/5

ASJC Scopus subject areas

  • 電子工学および電気工学
  • 産業および生産工学
  • メディア記述

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