Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/118714
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dc.contributorDepartment of Electrical and Electronic Engineering-
dc.contributorResearch Institute for Smart Energy-
dc.contributorPolicy Research Centre for Innovation and Technology-
dc.contributorInternational Centre of Urban Energy Nexus-
dc.contributorMainland Development Office-
dc.creatorMa, R-
dc.creatorBu, S-
dc.date.accessioned2026-05-13T02:01:06Z-
dc.date.available2026-05-13T02:01:06Z-
dc.identifier.urihttp://hdl.handle.net/10397/118714-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication R. Ma and S. Bu, 'Design of Joint Cyberattacks on Electric Vehicle Charging via Pricing and Traffic Manipulation to Threaten Secure Operation of Power Systems,' in IEEE Transactions on Transportation Electrification, vol. 12, no. 1, pp. 1955-1969, Feb. 2026 is available at https://doi.org/10.1109/TTE.2025.3636234.en_US
dc.subjectCharging priceen_US
dc.subjectCyberattacksen_US
dc.subjectElectric vehicle (EV)en_US
dc.subjectElectric vehicle charging navigation system (EVCNS)en_US
dc.subjectRoute planningen_US
dc.titleDesign of joint cyberattacks on electric vehicle charging via pricing and traffic manipulation to threaten secure operation of power systemsen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationTitle on author's file: Design of Joint Cyber-Attacks on Electric Vehicle Charging via Pricing and Traffic Manipulation to Threaten Secure Operation of Power Systems-
dc.identifier.spage1955-
dc.identifier.epage1969-
dc.identifier.volume12-
dc.identifier.issue1-
dc.identifier.doi10.1109/TTE.2025.3636234-
dcterms.abstractThe rapid development of electric vehicles (EVs) has strengthened the coupling between transportation and power systems. Meanwhile, the continuous growth in demand for EV charging would significantly impact the secure operation of power systems. Considering the vulnerability of vehicle navigation communication networks, this paper proposes a novel and practical joint cyber-attack scheme to manipulate the charging and route planning results of EV charging navigation. This cyber-attack can minimize both the charging price at the target EV charging station (EVCS) and the driving time required to reach the target EVCS, thus threatening the secure operation of power systems by attracting excessive EVs to charge at the target EVCS. Firstly, a two-level optimization model is proposed to identify the target EVCS based on the partially observable distribution network. This model identifies the EVCS that pose the greatest threat to the secure operation of power systems. Subsequently, a cyber-attack model is developed to manipulate the driving time of EVs to the target EVCS. The attack vector is designed to be stealthy to evade detection and sparse to minimize attack cost. Finally, based on the relationship between charging price and demand, an adaptive cyber-attack model for EV charging price is designed. When the joint cyber-attack is launched, EVs can be reasonably attracted to the target EVCS, regardless of the charging preferences of EV drivers. The coupled test system consisting of an IEEE 33-bus system and a 46-node transportation system verifies the effectiveness of the proposed methodology and model.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on transportation electrification, Feb. 2026, v. 12, no. 1, p. 1955-1969-
dcterms.isPartOfIEEE transactions on transportation electrification-
dcterms.issued2026-02-
dc.identifier.scopus2-s2.0-105023310763-
dc.identifier.eissn2332-7782-
dc.description.validate202605 bcjz-
dc.description.oaAccepted Manuscripten_US
dc.identifier.SubFormIDG001660/2026-01en_US
dc.description.fundingSourceRGCen_US
dc.description.fundingTextThis work was supported by the Hong Kong Research Grant Council for the Research Project under Grant 15205424.en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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