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

Tomotaka Inoue, Kento Hasegawa, Masao Yanagisawa, Nozomu Togawa

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

17 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 12th International Conference on ASIC, ASICON 2017
EditorsYajie Qin, Zhiliang Hong, Ting-Ao Tang
PublisherIEEE Computer Society
Pages811-814
Number of pages4
ISBN (Electronic)9781509066247
DOIs
Publication statusPublished - 2017 Jul 1
Event12th IEEE International Conference on Advanced Semiconductor Integrated Circuits, ASICON 2017 - Guiyang, China
Duration: 2017 Oct 252017 Oct 28

Publication series

NameProceedings of International Conference on ASIC
Volume2017-October
ISSN (Print)2162-7541
ISSN (Electronic)2162-755X

Other

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

Keywords

  • Design time
  • Gate-level netlist
  • Hardware Trojan
  • Machine learning
  • Support vector machine

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering

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