A survey of artificial intelligence-related cybersecurity risks and countermeasures in Mobility-as-a-Service

dc.contributor.authorChu, Kai-Fung
dc.contributor.authorYuan, Haiyue
dc.contributor.authorYuan, Jinsheng
dc.contributor.authorGuo, Weisi
dc.contributor.authorBalta-Ozkan, Nazmiye
dc.contributor.authorLi, Shujun
dc.date.accessioned2024-08-27T15:47:44Z
dc.date.available2024-08-27T15:47:44Z
dc.date.freetoread2024-08-27
dc.date.issued2024-11
dc.date.pubOnline2024-08-05
dc.description.abstractMobility-as-a-service (MaaS) integrates different transport modalities and can support more personalization of travelers’ journey planning based on their individual preferences, behaviors and wishes. To fully achieve the potential of MaaS, a range of artificial intelligence (AI) (including machine learning and data mining) algorithms are needed to learn personal requirements and needs to optimize the journey planning of each traveler and all travelers as a whole, to help transport service operators and relevant governmental bodies to operate and plan their services, and to detect and prevent cyberattacks from various threat actors, including dishonest and malicious travelers and transport operators. The increasing use of different AI and data processing algorithms in both centralized and distributed settings opens the MaaS ecosystem up to diverse cyber and privacy attacks at both the AI algorithm level and the connectivity surfaces. In this article, we present the first comprehensive review on the coupling between AI-driven MaaS design and the diverse cybersecurity challenges related to cyberattacks and countermeasures. In particular, we focus on how current and emerging AI-facilitated privacy risks (profiling, inference, and third-party threats) and adversarial AI attacks (evasion, extraction, and gamification) may impact the MaaS ecosystem. These risks often combine novel attacks (e.g., inverse learning) with traditional attack vectors (e.g., man-in-the-middle attacks), exacerbating the risks for the wider participation actors and the emergence of new business models.
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)
dc.description.sponsorshipThis work was supported by the Engineering and Physical Sciences Research Council (EPSRC), part of the UK Research and Innovation (UKRI), as part of the research projects “MACRO – Mobility as a service: Managing Cybersecurity Risks across Consumers, Organisations and Sectors” (EP/V039164/1), and “TAS-S: Trustworthy Autonomous Systems: Security” (EP/V026763/1).
dc.format.extent37-55
dc.identifier.citationChu K-F, Yuan H, Yuan J, et al., (2024) A survey of artificial intelligence-related cybersecurity risks and countermeasures in Mobility-as-a-Service. IEEE Intelligent Transportation Systems Magazine, Volume 16, Issue 6, November - December 2024, pp. 37-55
dc.identifier.eissn1941-1197
dc.identifier.elementsID549546
dc.identifier.issn1939-1390
dc.identifier.issueNo6
dc.identifier.urihttps://doi.org/10.1109/mits.2024.3427655
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/22831
dc.identifier.volumeNo16
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.publisher.urihttps://ieeexplore.ieee.org/document/10623343
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectArtificial intelligence
dc.subjectPlanning
dc.subjectBiological system modeling
dc.subjectMobility as a service
dc.subjectEcosystems
dc.subjectReviews
dc.subjectSurveys
dc.subject3509 Transportation, Logistics and Supply Chains
dc.subject40 Engineering
dc.subject4008 Electrical Engineering
dc.subject35 Commerce, Management, Tourism and Services
dc.subjectMachine Learning and Artificial Intelligence
dc.subject3509 Transportation, logistics and supply chains
dc.subject4008 Electrical engineering
dc.titleA survey of artificial intelligence-related cybersecurity risks and countermeasures in Mobility-as-a-Service
dc.typeArticle
dc.type.subtypeArticle
dc.type.subtypeEarly Access
dcterms.dateAccepted2024-07-04

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