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Collaborative Analysis Framework of Safety and Security for Autonomous Vehicles

Jin Cui Orcid Logo, Giedre Sabaliauskaite Orcid Logo, Lin Shen Liew, Fengjun Zhou, Biao Zhang

IEEE Access, Volume: 7, Pages: 148672 - 148683

Swansea University Author: Giedre Sabaliauskaite Orcid Logo

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DOI (Published version): 10.1109/access.2019.2946632

Abstract

Human error has been statistically proven to be the primary cause of road accidents. This undoubtedly is a contributory cause of the rising popularity of autonomous vehicles as they are presumably able to maneuver appropriately/optimally on the roads while diminishing the likelihood of human error a...

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Published in: IEEE Access
ISSN: 2169-3536
Published: Institute of Electrical and Electronics Engineers (IEEE) 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa61840
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first_indexed 2022-11-25T15:08:44Z
last_indexed 2023-01-13T19:22:52Z
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spelling 2022-11-25T15:10:17.4284025 v2 61840 2022-11-09 Collaborative Analysis Framework of Safety and Security for Autonomous Vehicles 6a674e2dbda3ec5f20599ce38199a7c3 0000-0003-1183-7001 Giedre Sabaliauskaite Giedre Sabaliauskaite true false 2022-11-09 SCS Human error has been statistically proven to be the primary cause of road accidents. This undoubtedly is a contributory cause of the rising popularity of autonomous vehicles as they are presumably able to maneuver appropriately/optimally on the roads while diminishing the likelihood of human error and its repercussion. However, autonomous vehicles are not ready for widespread adoption because their safety and security issues are yet to be thoroughly investigated/addressed. Little literature could be found on collaborative analysis of safety and security of autonomous vehicles. This paper proposes a framework for analyzing both safety and security issues, which includes an integrated safety and security method (S&S) with international vehicle safety and security standards ISO 26262 and SAE J3061. The applicability of the proposed framework is demonstrated using an example of typical autonomous vehicle model. Using this framework, one can clearly understand the vehicle functions, structure, the associated failures and attacks, and also see the vulnerabilities that are not yet addressed by countermeasures, which helps to improve the in-vehicle safety and security from researching and engineering perspectives. Journal Article IEEE Access 7 148672 148683 Institute of Electrical and Electronics Engineers (IEEE) 2169-3536 14 10 2019 2019-10-14 10.1109/access.2019.2946632 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2022-11-25T15:10:17.4284025 2022-11-09T22:45:21.1361056 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Jin Cui 0000-0002-8416-4728 1 Giedre Sabaliauskaite 0000-0003-1183-7001 2 Lin Shen Liew 3 Fengjun Zhou 4 Biao Zhang 5 61840__25914__6e33836055934be9be049745ca7e0b66.pdf 61840.pdf 2022-11-25T15:09:23.3568572 Output 11026721 application/pdf Version of Record true This work is licensed under a Creative Commons Attribution 4.0 License true eng http://creativecommons.org/licenses/by/4.0/
title Collaborative Analysis Framework of Safety and Security for Autonomous Vehicles
spellingShingle Collaborative Analysis Framework of Safety and Security for Autonomous Vehicles
Giedre Sabaliauskaite
title_short Collaborative Analysis Framework of Safety and Security for Autonomous Vehicles
title_full Collaborative Analysis Framework of Safety and Security for Autonomous Vehicles
title_fullStr Collaborative Analysis Framework of Safety and Security for Autonomous Vehicles
title_full_unstemmed Collaborative Analysis Framework of Safety and Security for Autonomous Vehicles
title_sort Collaborative Analysis Framework of Safety and Security for Autonomous Vehicles
author_id_str_mv 6a674e2dbda3ec5f20599ce38199a7c3
author_id_fullname_str_mv 6a674e2dbda3ec5f20599ce38199a7c3_***_Giedre Sabaliauskaite
author Giedre Sabaliauskaite
author2 Jin Cui
Giedre Sabaliauskaite
Lin Shen Liew
Fengjun Zhou
Biao Zhang
format Journal article
container_title IEEE Access
container_volume 7
container_start_page 148672
publishDate 2019
institution Swansea University
issn 2169-3536
doi_str_mv 10.1109/access.2019.2946632
publisher Institute of Electrical and Electronics Engineers (IEEE)
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 Human error has been statistically proven to be the primary cause of road accidents. This undoubtedly is a contributory cause of the rising popularity of autonomous vehicles as they are presumably able to maneuver appropriately/optimally on the roads while diminishing the likelihood of human error and its repercussion. However, autonomous vehicles are not ready for widespread adoption because their safety and security issues are yet to be thoroughly investigated/addressed. Little literature could be found on collaborative analysis of safety and security of autonomous vehicles. This paper proposes a framework for analyzing both safety and security issues, which includes an integrated safety and security method (S&S) with international vehicle safety and security standards ISO 26262 and SAE J3061. The applicability of the proposed framework is demonstrated using an example of typical autonomous vehicle model. Using this framework, one can clearly understand the vehicle functions, structure, the associated failures and attacks, and also see the vulnerabilities that are not yet addressed by countermeasures, which helps to improve the in-vehicle safety and security from researching and engineering perspectives.
published_date 2019-10-14T04:20:58Z
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score 11.037603

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