Hardware-trojan classification based on the structure of trigger circuits utilizing random forests

Tatsuki Kurihara, Nozomu Togawa

研究成果

抄録

Recently, with the spread of Internet of Things (IoT) devices, embedded hardware devices have been used in a variety of everyday electrical items. Due to the increased demand for embedded hardware devices, some of the IC design and manufacturing steps have been outsourced to third-party vendors. Since malicious third-party vendors may insert malicious circuits, called hardware Trojans, into their products, developing an effective hardware Trojan detection method is strongly required. In this paper, we propose 25 hardware-Trojan features based on the structure of trigger circuits for machine-learning-based hardware Trojan detection. Combining the proposed features into 11 existing hardware-Trojan features, we totally utilize 36 hardware-Trojan features for classification. Then we classify the nets in an unknown netlist into a set of normal nets and Trojan nets based on the random-forest classifier. The experimental results demonstrate that the average true positive rate (TPR) becomes 63.6% and the average true negative rate (TNR) becomes 100.0%. They improve the average TPR by 14.7 points while keeping the average TNR compared to existing state-of-the-art methods. In particular, the proposed method successfully finds out Trojan nets in several benchmark circuits, which are not found by the existing method.

本文言語English
ホスト出版物のタイトルProceedings - 2021 IEEE 27th International Symposium on On-Line Testing and Robust System Design, IOLTS 2021
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781665433709
DOI
出版ステータスPublished - 2021 6 28
イベント27th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2021 - Virtual, Online
継続期間: 2021 6 282021 6 30

出版物シリーズ

名前Proceedings - 2021 IEEE 27th International Symposium on On-Line Testing and Robust System Design, IOLTS 2021

Conference

Conference27th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2021
CityVirtual, Online
Period21/6/2821/6/30

ASJC Scopus subject areas

  • ソフトウェア
  • エネルギー工学および電力技術
  • 電子工学および電気工学
  • 安全性、リスク、信頼性、品質管理
  • 人工知能
  • 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

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