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WOLVES: Window of Opportunity attack feasibility likelihood value estimation through a simulation-based approach

Suraj Harsha Kamtam Orcid Logo, Qian Lu Orcid Logo, Abdur Rakib Orcid Logo, Muhamad Azfar Ramli Orcid Logo, Rakhi Manohar Mepparambath Orcid Logo, Siraj Shaikh Orcid Logo, Hoang Nguyen Orcid Logo

Computers & Security, Volume: 157, Start page: 104549

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

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DOI (Published version): 10.1016/j.cose.2025.104549

Abstract

The Road Vehicles Cybersecurity Engineering Standard, ISO/SAE 21434, provides a framework for road vehicle Threat Analysis and Risk Assessment (TARA). The TARA framework must include Connected Vehicles (CVs) and their connectivity with external interfaces. However, assessing cyber-attack feasibility...

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Published in: Computers & Security
ISSN: 0167-4048 1872-6208
Published: Elsevier BV 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa69751
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The TARA framework must include Connected Vehicles (CVs) and their connectivity with external interfaces. However, assessing cyber-attack feasibility on CVs is a significant challenge, as traditionally, qualitative and subjective expert opinions are the norm. Additionally, there is a need for historical data on security-related incidents and dynamically evolving interconnected vehicle-to-everything (V2X) entities for feasibility assessment, which is not readily available. To address this problem, this paper presents, to the best of our knowledge, the first simulation-based TARA framework designed to characterise, quantify, and assess the Window of Opportunity (WO) for attackers&#x2014;a metric that indicates the likelihood of an attack. A case study involving Bluetooth, with one attacker and one target, is modelled to demonstrate the proposed framework WOLVES&#x2019;s applicability. Two scenarios have been investigated using different motorway roads in the UK. 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spelling 2025-07-21T12:00:07.2785027 v2 69751 2025-06-17 WOLVES: Window of Opportunity attack feasibility likelihood value estimation through a simulation-based approach 50117e8faac2d0937989e14847105704 0000-0002-0726-3319 Siraj Shaikh Siraj Shaikh true false cb24d5c5080534dc5b5e3390f24dd422 0000-0003-0260-1697 Hoang Nguyen Hoang Nguyen true false 2025-06-17 MACS The Road Vehicles Cybersecurity Engineering Standard, ISO/SAE 21434, provides a framework for road vehicle Threat Analysis and Risk Assessment (TARA). The TARA framework must include Connected Vehicles (CVs) and their connectivity with external interfaces. However, assessing cyber-attack feasibility on CVs is a significant challenge, as traditionally, qualitative and subjective expert opinions are the norm. Additionally, there is a need for historical data on security-related incidents and dynamically evolving interconnected vehicle-to-everything (V2X) entities for feasibility assessment, which is not readily available. To address this problem, this paper presents, to the best of our knowledge, the first simulation-based TARA framework designed to characterise, quantify, and assess the Window of Opportunity (WO) for attackers—a metric that indicates the likelihood of an attack. A case study involving Bluetooth, with one attacker and one target, is modelled to demonstrate the proposed framework WOLVES’s applicability. Two scenarios have been investigated using different motorway roads in the UK. The primary outcome is the WOLVES framework, which employs a data-driven approach using both prior and likelihood information to estimate the probability of a successful cyber attack on a given technology in CVs. The findings from this research could assist threat analysts, decision-makers, and planners involved in CV risk assessment by enhancing the modelling of attack feasibility for cybersecurity threats in dynamic scenarios and developing appropriate mitigation strategies. Journal Article Computers &amp; Security 157 104549 Elsevier BV 0167-4048 1872-6208 Bluetooth communication; Attack feasibility assessment; Dynamic threat assessment; Vehicular Network Simulations; Window of Opportunity; Automotive cybersecurity 1 10 2025 2025-10-01 10.1016/j.cose.2025.104549 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University Another institution paid the OA fee This work was supported by Coventry University and the A*STAR Research Attachment Programme (ARAP) . 2025-07-21T12:00:07.2785027 2025-06-17T11:21:47.2798800 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Suraj Harsha Kamtam 0000-0003-4687-796x 1 Qian Lu 0000-0001-8235-853x 2 Abdur Rakib 0000-0001-5430-450x 3 Muhamad Azfar Ramli 0000-0002-6321-0828 4 Rakhi Manohar Mepparambath 0000-0003-3308-7838 5 Siraj Shaikh 0000-0002-0726-3319 6 Hoang Nguyen 0000-0003-0260-1697 7 69751__34803__fc97ebb4d7d04d5ba49ac148b0b3a8fb.pdf 69751.VoR.pdf 2025-07-21T11:56:51.4300246 Output 3569992 application/pdf Version of Record true © 2025 The Authors. This is an open access article under the CC BY license. true eng http://creativecommons.org/licenses/by/4.0/
title WOLVES: Window of Opportunity attack feasibility likelihood value estimation through a simulation-based approach
spellingShingle WOLVES: Window of Opportunity attack feasibility likelihood value estimation through a simulation-based approach
Siraj Shaikh
Hoang Nguyen
title_short WOLVES: Window of Opportunity attack feasibility likelihood value estimation through a simulation-based approach
title_full WOLVES: Window of Opportunity attack feasibility likelihood value estimation through a simulation-based approach
title_fullStr WOLVES: Window of Opportunity attack feasibility likelihood value estimation through a simulation-based approach
title_full_unstemmed WOLVES: Window of Opportunity attack feasibility likelihood value estimation through a simulation-based approach
title_sort WOLVES: Window of Opportunity attack feasibility likelihood value estimation through a simulation-based approach
author_id_str_mv 50117e8faac2d0937989e14847105704
cb24d5c5080534dc5b5e3390f24dd422
author_id_fullname_str_mv 50117e8faac2d0937989e14847105704_***_Siraj Shaikh
cb24d5c5080534dc5b5e3390f24dd422_***_Hoang Nguyen
author Siraj Shaikh
Hoang Nguyen
author2 Suraj Harsha Kamtam
Qian Lu
Abdur Rakib
Muhamad Azfar Ramli
Rakhi Manohar Mepparambath
Siraj Shaikh
Hoang Nguyen
format Journal article
container_title Computers &amp; Security
container_volume 157
container_start_page 104549
publishDate 2025
institution Swansea University
issn 0167-4048
1872-6208
doi_str_mv 10.1016/j.cose.2025.104549
publisher Elsevier BV
college_str Faculty of Science and Engineering
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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
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description The Road Vehicles Cybersecurity Engineering Standard, ISO/SAE 21434, provides a framework for road vehicle Threat Analysis and Risk Assessment (TARA). The TARA framework must include Connected Vehicles (CVs) and their connectivity with external interfaces. However, assessing cyber-attack feasibility on CVs is a significant challenge, as traditionally, qualitative and subjective expert opinions are the norm. Additionally, there is a need for historical data on security-related incidents and dynamically evolving interconnected vehicle-to-everything (V2X) entities for feasibility assessment, which is not readily available. To address this problem, this paper presents, to the best of our knowledge, the first simulation-based TARA framework designed to characterise, quantify, and assess the Window of Opportunity (WO) for attackers—a metric that indicates the likelihood of an attack. A case study involving Bluetooth, with one attacker and one target, is modelled to demonstrate the proposed framework WOLVES’s applicability. Two scenarios have been investigated using different motorway roads in the UK. The primary outcome is the WOLVES framework, which employs a data-driven approach using both prior and likelihood information to estimate the probability of a successful cyber attack on a given technology in CVs. The findings from this research could assist threat analysts, decision-makers, and planners involved in CV risk assessment by enhancing the modelling of attack feasibility for cybersecurity threats in dynamic scenarios and developing appropriate mitigation strategies.
published_date 2025-10-01T05:28:59Z
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