{"title":"EPCM: Efficient privacy-preserving charging matching scheme with data integrity for electric vehicles","authors":"Tingting Jin, Peng Hu, Kaizhong Zuo, Tianjiao Ni, Dong Xie, Zhangyi Shen, Fulong Chen","doi":"10.1016/j.pmcj.2025.102042","DOIUrl":null,"url":null,"abstract":"<div><div>Compared to traditional charging stations, the Vehicle-to-Vehicle (V2V) charging mode can expand the coverage of the charging network and is expected to become an important supplementary method for future electric vehicle charging. However, the leakage of location privacy in charging matching has become one of the main concerns of users. To tackle this problem, we propose an efficient privacy preserving charging matching scheme, named EPCM, which ensures data integrity without compromising the location privacy of vehicles. Firstly, we utilize the modified Paillier cryptosystem and identity based batch signature to achieve location privacy and data integrity. Secondly, our scheme operates in a round-by-round manner, ensuring immediate task completion and allowing vehicles to dynamically join or leave. The security proof and analysis indicates that EPCM can achieve security features including confidentiality, location privacy, authentication, and data integrity. Furthermore, by carrying out extensive experiments, the experimental results demonstrate that our scheme performs excellently in terms of computational and communication overhead, as well as total transmission delay.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102042"},"PeriodicalIF":3.0000,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pervasive and Mobile Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574119225000318","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
EPCM: Efficient privacy-preserving charging matching scheme with data integrity for electric vehicles
Compared to traditional charging stations, the Vehicle-to-Vehicle (V2V) charging mode can expand the coverage of the charging network and is expected to become an important supplementary method for future electric vehicle charging. However, the leakage of location privacy in charging matching has become one of the main concerns of users. To tackle this problem, we propose an efficient privacy preserving charging matching scheme, named EPCM, which ensures data integrity without compromising the location privacy of vehicles. Firstly, we utilize the modified Paillier cryptosystem and identity based batch signature to achieve location privacy and data integrity. Secondly, our scheme operates in a round-by-round manner, ensuring immediate task completion and allowing vehicles to dynamically join or leave. The security proof and analysis indicates that EPCM can achieve security features including confidentiality, location privacy, authentication, and data integrity. Furthermore, by carrying out extensive experiments, the experimental results demonstrate that our scheme performs excellently in terms of computational and communication overhead, as well as total transmission delay.
期刊介绍:
As envisioned by Mark Weiser as early as 1991, pervasive computing systems and services have truly become integral parts of our daily lives. Tremendous developments in a multitude of technologies ranging from personalized and embedded smart devices (e.g., smartphones, sensors, wearables, IoTs, etc.) to ubiquitous connectivity, via a variety of wireless mobile communications and cognitive networking infrastructures, to advanced computing techniques (including edge, fog and cloud) and user-friendly middleware services and platforms have significantly contributed to the unprecedented advances in pervasive and mobile computing. Cutting-edge applications and paradigms have evolved, such as cyber-physical systems and smart environments (e.g., smart city, smart energy, smart transportation, smart healthcare, etc.) that also involve human in the loop through social interactions and participatory and/or mobile crowd sensing, for example. The goal of pervasive computing systems is to improve human experience and quality of life, without explicit awareness of the underlying communications and computing technologies.
The Pervasive and Mobile Computing Journal (PMC) is a high-impact, peer-reviewed technical journal that publishes high-quality scientific articles spanning theory and practice, and covering all aspects of pervasive and mobile computing and systems.