Qian Mei , Wenxia Guo , Yanan Zhao , Liming Nie , Deepak Adhikari
{"title":"Blockchain-based privacy-preserving incentive scheme for internet of electric vehicle","authors":"Qian Mei , Wenxia Guo , Yanan Zhao , Liming Nie , Deepak Adhikari","doi":"10.1016/j.inffus.2024.102732","DOIUrl":null,"url":null,"abstract":"<div><div>The emerging proportion of renewable energy resources penetration and the rapid popularity of Electric Vehicles (EVs) have promoted the development of the Internet of Electric Vehicles (IoEV), which enables seamless EV’ information collection and energy delivery by leveraging wireless power transfer. However, vulnerabilities in internet infrastructure and the self-interested behavior of EVs pose significant security and privacy risks during energy delivery in IoEV. In addition, EVs often lack the incentive to cooperate for regional energy balance. To tackle these questions, this paper proposes a blockchain-based privacy-preserving incentive mechanism for energy delivery in IoEV. Based on cryptographic technology, this paper introduces a group signature scheme with self-controlled and sequential linkability, which safeguards the privacy of EV users and ensures transaction records maintain exact sequence during energy delivery. Furthermore, an incentive mechanism based on co-utile reputation management is presented to encourage EV users to participate honestly and cooperatively in energy delivery. Moreover, a comprehensive security analysis of the proposed group signature scheme and incentive mechanism is given. Finally, extensive experimental results demonstrate the feasibility and efficiency of the proposed approach compared to existing schemes.</div></div>","PeriodicalId":50367,"journal":{"name":"Information Fusion","volume":"115 ","pages":"Article 102732"},"PeriodicalIF":14.7000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Fusion","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1566253524005104","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
The emerging proportion of renewable energy resources penetration and the rapid popularity of Electric Vehicles (EVs) have promoted the development of the Internet of Electric Vehicles (IoEV), which enables seamless EV’ information collection and energy delivery by leveraging wireless power transfer. However, vulnerabilities in internet infrastructure and the self-interested behavior of EVs pose significant security and privacy risks during energy delivery in IoEV. In addition, EVs often lack the incentive to cooperate for regional energy balance. To tackle these questions, this paper proposes a blockchain-based privacy-preserving incentive mechanism for energy delivery in IoEV. Based on cryptographic technology, this paper introduces a group signature scheme with self-controlled and sequential linkability, which safeguards the privacy of EV users and ensures transaction records maintain exact sequence during energy delivery. Furthermore, an incentive mechanism based on co-utile reputation management is presented to encourage EV users to participate honestly and cooperatively in energy delivery. Moreover, a comprehensive security analysis of the proposed group signature scheme and incentive mechanism is given. Finally, extensive experimental results demonstrate the feasibility and efficiency of the proposed approach compared to existing schemes.
期刊介绍:
Information Fusion serves as a central platform for showcasing advancements in multi-sensor, multi-source, multi-process information fusion, fostering collaboration among diverse disciplines driving its progress. It is the leading outlet for sharing research and development in this field, focusing on architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome.