Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/117198
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Title: Vulnerability assessment of large-scale urban road network under emerging disinformation attacks
Authors: Meng, Y 
Zhao, X
Xu, X 
Ma, W 
Issue Date: 2025
Source: Transportmetrica. A, Transport science, Published online: 16 Apr 2025, Latest Articles, https://doi.org/10.1080/23249935.2025.2491446
Abstract: Transportation Cyber-Physical Systems (TCPS) are facing an emerging cyber threat from disinformation attacks that can manipulate individual cognition and behaviours, potentially making urban transportation vulnerable. Traditional studies on road network vulnerability have primarily focussed on physical attacks like node or link removal, with little attention to disinformation attacks. To fill this gap, this study introduces a novel disinformation attack mode for road TCPS. It hacks navigation applications by strategically modifying the link cost information, thereby affecting drivers' routing decisions. Crucially, this attack mode leaves the physical topology of TCPS-based road networks unchanged, impacting only the cyber layer's information. Additionally, intriguing link metrics, like the partial derivative of total travel time to link flow, are introduced to identify attack targets. On this basis, we design multi-strategy disinformation attacks to assess road network vulnerability. The proposed research framework, validated by San Francisco's large-scale urban road network, reveals that disinformation attacks on just 0.12% of links could cause an annual city-wide economic loss of $79.26 million in the worst-case scenario. This study offers a unique viewpoint on road network vulnerability, emphasising the vital need for TCPS cybersecurity to ensure urban transportation's reliability and resilience.
Keywords: Disinformation attacks
Large-scale road network
Transportation cyber-physical system
Vulnerability assessment
Publisher: Taylor & Francis
Journal: Transportmetrica. A, Transport science 
ISSN: 2324-9935
EISSN: 2324-9943
DOI: 10.1080/23249935.2025.2491446
Rights: © 2025 Hong Kong Society for Transportation Studies Limited
This is an Accepted Manuscript of an article published by Taylor & Francis in Transportmetrica A: Transport Science on 16 Apr. 2025 (published online), available at: https://doi.org/10.1080/23249935.2025.2491446.
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