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

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

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

5 Citations (Scopus)

Abstract

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%.

Original languageEnglish
Title of host publication2018 IEEE 8th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018
PublisherIEEE Computer Society
ISBN (Electronic)9781538660959
DOIs
Publication statusPublished - 2018 Dec 13
Event8th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018 - Berlin, Germany
Duration: 2018 Sep 22018 Sep 5

Publication series

NameIEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Volume2018-September
ISSN (Print)2166-6814
ISSN (Electronic)2166-6822

Other

Other8th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018
Country/TerritoryGermany
CityBerlin
Period18/9/218/9/5

Keywords

  • design time
  • gate-level netlist
  • hardware Trojan
  • machine learning
  • neural network

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Media Technology

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