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Systematic Risk Characterisation of Hardware Threats to Automotive System

James Pickford Orcid Logo, Rasadhi Attale Orcid Logo, Siraj Shaikh Orcid Logo, Hoang Nguyen Orcid Logo, Lee Harrison Orcid Logo

ACM Journal on Autonomous Transportation Systems

Swansea University Authors: Siraj Shaikh Orcid Logo, Hoang Nguyen Orcid Logo

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DOI (Published version): 10.1145/3661315

Abstract

The increasing dependence of modern automotive systems on electronics and software poses cybersecurity risks previously not factored into design and engineering of such systems. Attacks on hardware components, communication modules and embedded software – many of which are purposefully designed for...

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Published in: ACM Journal on Autonomous Transportation Systems
ISSN: 2833-0528
Published: Association for Computing Machinery (ACM)
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URI: https://cronfa.swan.ac.uk/Record/cronfa66221
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first_indexed 2024-04-30T13:01:38Z
last_indexed 2024-04-30T13:01:38Z
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spelling v2 66221 2024-04-30 Systematic Risk Characterisation of Hardware Threats to Automotive System 50117e8faac2d0937989e14847105704 0000-0002-0726-3319 Siraj Shaikh Siraj Shaikh true false cb24d5c5080534dc5b5e3390f24dd422 0000-0003-0260-1697 Hoang Nguyen Hoang Nguyen true false 2024-04-30 MACS The increasing dependence of modern automotive systems on electronics and software poses cybersecurity risks previously not factored into design and engineering of such systems. Attacks on hardware components, communication modules and embedded software – many of which are purposefully designed for automotive control and communications – are the key focus of this paper. We adopt a novel approach to characterise such attacks using Gajski-Kuhn Y-charts to represent attack manipulation across behavioural, structural and physical domains. Our selection of attacks is evidence-driven demonstrating threats that have been demonstrated to be feasible in the real-world. We then risk assess impact of such threats using the recently adopted ISO/SAE 21434 standard for automotive cybersecurity risk assessment, including mitigations for potential adoption. Our work serves to provide unique insights into the complex dynamic of hardware vulnerabilities and how the industry may address system-level security and protection of modern automotive platforms. Journal Article ACM Journal on Autonomous Transportation Systems Association for Computing Machinery (ACM) 2833-0528 0 0 0 0001-01-01 10.1145/3661315 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University 2024-05-07T17:09:28.7660881 2024-04-30T13:56:30.9438881 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science James Pickford 0009-0000-9243-7397 1 Rasadhi Attale 0009-0000-3285-8210 2 Siraj Shaikh 0000-0002-0726-3319 3 Hoang Nguyen 0000-0003-0260-1697 4 Lee Harrison 0009-0000-4690-1574 5 66221__30192__62725cb58d0d43fa9473825a9fde7d23.pdf 66221.pdf 2024-04-30T14:01:26.8391089 Output 897716 application/pdf Accepted Manuscript true Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy (rights retention). true eng https://creativecommons.org/licenses/by/4.0/deed.en
title Systematic Risk Characterisation of Hardware Threats to Automotive System
spellingShingle Systematic Risk Characterisation of Hardware Threats to Automotive System
Siraj Shaikh
Hoang Nguyen
title_short Systematic Risk Characterisation of Hardware Threats to Automotive System
title_full Systematic Risk Characterisation of Hardware Threats to Automotive System
title_fullStr Systematic Risk Characterisation of Hardware Threats to Automotive System
title_full_unstemmed Systematic Risk Characterisation of Hardware Threats to Automotive System
title_sort Systematic Risk Characterisation of Hardware Threats to Automotive System
author_id_str_mv 50117e8faac2d0937989e14847105704
cb24d5c5080534dc5b5e3390f24dd422
author_id_fullname_str_mv 50117e8faac2d0937989e14847105704_***_Siraj Shaikh
cb24d5c5080534dc5b5e3390f24dd422_***_Hoang Nguyen
author Siraj Shaikh
Hoang Nguyen
author2 James Pickford
Rasadhi Attale
Siraj Shaikh
Hoang Nguyen
Lee Harrison
format Journal article
container_title ACM Journal on Autonomous Transportation Systems
institution Swansea University
issn 2833-0528
doi_str_mv 10.1145/3661315
publisher Association for Computing Machinery (ACM)
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
description The increasing dependence of modern automotive systems on electronics and software poses cybersecurity risks previously not factored into design and engineering of such systems. Attacks on hardware components, communication modules and embedded software – many of which are purposefully designed for automotive control and communications – are the key focus of this paper. We adopt a novel approach to characterise such attacks using Gajski-Kuhn Y-charts to represent attack manipulation across behavioural, structural and physical domains. Our selection of attacks is evidence-driven demonstrating threats that have been demonstrated to be feasible in the real-world. We then risk assess impact of such threats using the recently adopted ISO/SAE 21434 standard for automotive cybersecurity risk assessment, including mitigations for potential adoption. Our work serves to provide unique insights into the complex dynamic of hardware vulnerabilities and how the industry may address system-level security and protection of modern automotive platforms.
published_date 0001-01-01T17:09:27Z
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score 11.013731

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