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Hardware Trojans: Lessons Learned after One Decade of Research

Authors:

M. TehranipoorAuthors Info & Claims

ACM Transactions on Design Automation of Electronic Systems (TODAES), Volume 22, Issue 1

Article No.: 6, Pages 1 - 23

https://doi.org/10.1145/2906147

Published: 27 May 2016 Publication History

Abstract

Given the increasing complexity of modern electronics and the cost of fabrication, entities from around the globe have become more heavily involved in all phases of the electronics supply chain. In this environment, hardware Trojans (i.e., malicious modifications or inclusions made by untrusted third parties) pose major security concerns, especially for those integrated circuits (ICs) and systems used in critical applications and cyber infrastructure. While hardware Trojans have been explored significantly in academia over the last decade, there remains room for improvement. In this article, we examine the research on hardware Trojans from the last decade and attempt to capture the lessons learned. A comprehensive adversarial model taxonomy is introduced and used to examine the current state of the art. Then the past countermeasures and publication trends are categorized based on the adversarial model and topic. Through this analysis, we identify what has been covered and the important problems that are underinvestigated. We also identify the most critical lessons for those new to the field and suggest a roadmap for future hardware Trojan research.

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Cited By

Podugu DKamala Kumari ASabbavarapu S(2024)Intellectual Property Design with PUF-based Hardware SecurityEngineering, Technology & Applied Science Research10.48084/etasr.741314:4(15559-15563)Online publication date: 2-Aug-2024
https://doi.org/10.48084/etasr.7413
Hou JLiu ZYang ZYang C(2024)Hardware Trojan Attacks on the Reconfigurable Interconnections of Field-Programmable Gate Array-Based Convolutional Neural Network Accelerators and a Physically Unclonable Function-Based Countermeasure Detection TechniqueMicromachines10.3390/mi1501014915:1(149)Online publication date: 19-Jan-2024
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Duque Antón AMüller JDeutschmann LFadiheh MStoffel DKunz W(2024)A Golden-Free Formal Method for Trojan Detection in Non-Interfering Accelerators2024 Design, Automation & Test in Europe Conference & Exhibition (DATE)10.23919/DATE58400.2024.10546664(1-6)Online publication date: 25-Mar-2024
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Index Terms

Hardware Trojans: Lessons Learned after One Decade of Research
1. Hardware
  1. Robustness
    1. Safety critical systems

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cover image ACM Transactions on Design Automation of Electronic Systems

ACM Transactions on Design Automation of Electronic Systems Volume 22, Issue 1

January 2017

463 pages

ISSN:1084-4309

EISSN:1557-7309

DOI:10.1145/2948199

Editor:
Naehyuck Chang
Korea Advanced Institute of Science and Technology, Korea

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Publication History

Published: 27 May 2016

Accepted: 01 March 2016

Revised: 01 January 2016

Received: 01 September 2015

Published in TODAES Volume 22, Issue 1

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Cited By

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https://doi.org/10.48084/etasr.7413
Hou JLiu ZYang ZYang C(2024)Hardware Trojan Attacks on the Reconfigurable Interconnections of Field-Programmable Gate Array-Based Convolutional Neural Network Accelerators and a Physically Unclonable Function-Based Countermeasure Detection TechniqueMicromachines10.3390/mi1501014915:1(149)Online publication date: 19-Jan-2024
https://doi.org/10.3390/mi15010149
Duque Antón AMüller JDeutschmann LFadiheh MStoffel DKunz W(2024)A Golden-Free Formal Method for Trojan Detection in Non-Interfering Accelerators2024 Design, Automation & Test in Europe Conference & Exhibition (DATE)10.23919/DATE58400.2024.10546664(1-6)Online publication date: 25-Mar-2024
https://doi.org/10.23919/DATE58400.2024.10546664
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Kande RPearce HTan BDolan-Gavitt BThakur SKarri RRajendran J(2024)(Security) Assertions by Large Language ModelsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.337280919(4374-4389)Online publication date: 2024
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Gohil VPatnaik SGuo HKalathil DRajendran J(2024)DETERRENT: Detecting Trojans Using Reinforcement LearningIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.330973143:1(57-70)Online publication date: 1-Jan-2024
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Mulhem SMuuss FEwert CBuchty RBerekovic M(2024)ML-Based Trojan Classification: Repercussions of Toxic Boundary NetsIEEE Embedded Systems Letters10.1109/LES.2023.333854316:3(251-254)Online publication date: Sep-2024
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