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Trusting the trust anchor: towards detecting cross-layer vulnerabilities with hardware fuzzing

Published: 23 August 2022 Publication History

Abstract

The rise in the development of complex and application-specific commercial and open-source hardware and the shrinking verification time are causing numerous hardware-security vulnerabilities. Traditional verification techniques are limited in both scalability and completeness. Research in this direction is hindered due to the lack of robust testing benchmarks. In this paper, in collaboration with our industry partners, we built an ecosystem mimicking the hardware-development cycle where we inject bugs inspired by real-world vulnerabilities into RISC-V SoC design and organized an open-to-all bug-hunting competition. We equipped the participating researchers with industry-standard static and dynamic verification tools in a ready-to-use environment. The findings from our competition shed light on the strengths and weaknesses of the existing verification tools and highlight the potential for future research in developing new vulnerability detection techniques.

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Cited By

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  • (2024)Jailbreaking Pre-trained Large Language Models Towards Hardware Vulnerability Insertion AbilityProceedings of the Great Lakes Symposium on VLSI 202410.1145/3649476.3658799(579-582)Online publication date: 12-Jun-2024
  • (2024)(Security) Assertions by Large Language ModelsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.337280919(4374-4389)Online publication date: 2024
  • (2024)Instiller: Toward Efficient and Realistic RTL FuzzingIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2024.336031843:7(2177-2190)Online publication date: Jul-2024
  • Show More Cited By

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cover image ACM Conferences
DAC '22: Proceedings of the 59th ACM/IEEE Design Automation Conference
July 2022
1462 pages
ISBN:9781450391429
DOI:10.1145/3489517
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 23 August 2022

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Author Tags

  1. CTF
  2. Hack@DAC
  3. Hack@EVENT
  4. fuzzing
  5. hardware competition
  6. hardware security

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  • Research-article

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DAC '22
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DAC '22: 59th ACM/IEEE Design Automation Conference
July 10 - 14, 2022
California, San Francisco

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Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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Cited By

View all
  • (2024)Jailbreaking Pre-trained Large Language Models Towards Hardware Vulnerability Insertion AbilityProceedings of the Great Lakes Symposium on VLSI 202410.1145/3649476.3658799(579-582)Online publication date: 12-Jun-2024
  • (2024)(Security) Assertions by Large Language ModelsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.337280919(4374-4389)Online publication date: 2024
  • (2024)Instiller: Toward Efficient and Realistic RTL FuzzingIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2024.336031843:7(2177-2190)Online publication date: Jul-2024
  • (2024)A Hardware Security Evaluation Platform on RISC-V SoC2024 IEEE International Test Conference in Asia (ITC-Asia)10.1109/ITC-Asia62534.2024.10661352(1-6)Online publication date: 18-Aug-2024
  • (2024)Research on Dynamic Fuzzy Testing in Securing Cloud Infrastructure based on Deep Learning2024 3rd International Conference on Cloud Computing, Big Data Application and Software Engineering (CBASE)10.1109/CBASE64041.2024.10824501(859-863)Online publication date: 11-Oct-2024
  • (2023)PSOFuzz: Fuzzing Processors with Particle Swarm Optimization2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323913(1-9)Online publication date: 28-Oct-2023

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