Hardware Trojans classification for gate-level netlists using multi-layer neural networks

研究成果: Conference contribution

58 被引用数 (Scopus)

抄録

Recently, due to the increase of outsourcing in IC design and manufacturing, it has been reported that malicious third-party IC vendors often insert hardware Trojans into their products. Especially in IC design step, it is strongly required to detect hardware Trojans because malicious third-party vendors can easily insert hardware Trojans in their products. In this paper, we propose a machine-learning-based hardware-Trojan detection method for gate-level netlists using multi-layer neural networks. First, we extract 11 Trojan-net feature values for each net in a netlist. After that, we classify the nets in an unknown netlist into a set of Trojan nets and that of normal nets using multi-layer neural networks. We obtained at most 100% true positive rate with our proposed method.

本文言語English
ホスト出版物のタイトル2017 IEEE 23rd International Symposium on On-Line Testing and Robust System Design, IOLTS 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ227-232
ページ数6
ISBN(電子版)9781538603512
DOI
出版ステータスPublished - 2017 9月 19
イベント23rd IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2017 - Thessaloniki, Greece
継続期間: 2017 7月 32017 7月 5

出版物シリーズ

名前2017 IEEE 23rd International Symposium on On-Line Testing and Robust System Design, IOLTS 2017

Other

Other23rd IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2017
国/地域Greece
CityThessaloniki
Period17/7/317/7/5

ASJC Scopus subject areas

  • 電子工学および電気工学
  • 安全性、リスク、信頼性、品質管理
  • 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
  • 制御およびシステム工学

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