DEMO: Adaptive Fuzz Testing for Automotive ECUs: A Modular Testbed Approach for Enhanced Vulnerability Detection

Manu Jo Varghese, Frank Jiang, Robin Doss, Adnan Anwar, Abdur Rakib

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

Abstract

This demonstration introduces an adaptive fuzzing physical test bed aimed at identifying vulnerabilities within automotive systems, specifically focusing on the Controller Area Network (CAN) bus. By employing "Automated Reverse Engineering-Guided Fuzzing"(ARE-GF), our framework evaluates the security resilience of the CAN network against sophisticated attacks. The demo showcases live demonstrations of the fuzzing process, the creation of the test bed using cost-effective electrical components, real-time ECU response analysis, and examples of discovered vulnerabilities, providing insights into advanced automotive cybersecurity testing methodologies.

Original languageEnglish
Title of host publicationACM SIGCOMM Posters and Demos '24
Subtitle of host publicationProceedings of the ACM SIGCOMM 2024 Conference: Posters and Demos
PublisherACM
Pages110-112
Number of pages3
Edition1
ISBN (Electronic)9798400707179
DOIs
Publication statusPublished - 5 Aug 2024
Event2024 SIGCOMM Poster and Demo Sessions, SIGCOMM Posters and Demos 2024 - Sydney, Australia
Duration: 4 Aug 20248 Aug 2024

Conference

Conference2024 SIGCOMM Poster and Demo Sessions, SIGCOMM Posters and Demos 2024
Country/TerritoryAustralia
CitySydney
Period4/08/248/08/24

Bibliographical note

Publisher Copyright:
© 2024 Copyright held by the owner/author(s).

Keywords

  • CAN bus
  • CAN security
  • CAN test-bed
  • vulnerability detection

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Software

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