CCUBI: A cross‐chain based premium competition scheme with privacy preservation for usage‐based insurance

International Journal of Intelligent SystemsEarly View RESEARCH ARTICLE CCUBI: A cross-chain based premium competition scheme with privacy preservation for usage-based insurance Longyang Yi, Longyang Yi orcid.org/0000-0003-0142-0755 Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, ChinaSearch for more papers by this authorYangyang Sun, Yangyang Sun orcid.org/0000-0003-0429-2146 Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, ChinaSearch for more papers by this authorBin Wang, Bin Wang orcid.org/0000-0002-0008-596X Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, ChinaSearch for more papers by this authorLi Duan, Li Duan orcid.org/0000-0002-1825-7416 Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, ChinaSearch for more papers by this authorHongliang Ma, Hongliang Ma School of Information Science and Technology, Shihezi University, Shihezi, ChinaSearch for more papers by this authorBin Wang, Bin Wang orcid.org/0000-0002-3790-2708 Zhejiang Key Laboratory of Multi-Dimensional Perception Technology, Application and Cybersecurity, Hangzhou, ChinaSearch for more papers by this authorZhen Han, Zhen Han Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, ChinaSearch for more papers by this authorWei Wang, Corresponding Author Wei Wang wangwei1@bjtu.edu.cn orcid.org/0000-0002-5974-1589 Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China Correspondence Wei Wang, Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China. Email: wangwei1@bjtu.edu.cnSearch for more papers by this author Longyang Yi, Longyang Yi orcid.org/0000-0003-0142-0755 Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, ChinaSearch for more papers by this authorYangyang Sun, Yangyang Sun orcid.org/0000-0003-0429-2146 Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, ChinaSearch for more papers by this authorBin Wang, Bin Wang orcid.org/0000-0002-0008-596X Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, ChinaSearch for more papers by this authorLi Duan, Li Duan orcid.org/0000-0002-1825-7416 Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, ChinaSearch for more papers by this authorHongliang Ma, Hongliang Ma School of Information Science and Technology, Shihezi University, Shihezi, ChinaSearch for more papers by this authorBin Wang, Bin Wang orcid.org/0000-0002-3790-2708 Zhejiang Key Laboratory of Multi-Dimensional Perception Technology, Application and Cybersecurity, Hangzhou, ChinaSearch for more papers by this authorZhen Han, Zhen Han Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, ChinaSearch for more papers by this authorWei Wang, Corresponding Author Wei Wang wangwei1@bjtu.edu.cn orcid.org/0000-0002-5974-1589 Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China Correspondence Wei Wang, Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China. Email: wangwei1@bjtu.edu.cnSearch for more papers by this author First published: 02 September 2022 https://doi.org/10.1002/int.23053Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Usage-based insurance (UBI) provides reasonable vehicle insurance premiums based on vehicle usage and driving behavior. In general, there are three major issues in realizing intelligent UBI systems. First, UBI evaluation mechanisms are not auditable to drivers. Insurers may thus deliberately adjust the UBI premiums. Second, the process of collecting driving data by insurers may lead to serious privacy breaches. Third, forging safer driving data for reducing insurance premiums may cause economic losses for insurers. To address these challenges, in this study, we propose CCUBI, a cross-chain-based premium competition scheme with privacy preservation for intelligent UBI systems. We introduce tamper-resistant blockchain and smart contracts to construct credible insurance mechanisms. The cross-chain technology connects these blockchains in the entire network to form an open premium competition scheme. Vehicle owners can assess designated insurers by sharing historical data with them to get a suitable CCUBI plan. In addition, we propose a data aggregation method used for CCUBI analysis with privacy preservation. Vehicle owners only publish proofs of the driving data. Proofs can still maintain privacy and computability in cross-chain flows. Finally, we adopt roadside units to detect forged driving data. We conduct a detailed security analysis. Experimental results also demonstrate the efficiency of CCUBI. Open Research DATA AVAILABILITY STATEMENT Data sharing is not applicable to this article as no new data were created or analyzed in this study. Early ViewOnline Version of Record before inclusion in an issue RelatedInformation