PIAS: Privacy-Preserving Incentive Announcement System based on Blockchain for Internet of Vehicles

• Main Authors: ZHAN, Yonghua, YANG, Yang, CHENG, Hongju, LUO, Xiangyang, GUAN, Zhuangshuang, DENG, Robert H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Authentication; Bitcoin; Blockchain; Blockchains; Fair Payment; Incentive Mechanism; Internet of Vehicles; Privacy; Privacy Preservation; Protocols; Reliability; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/9036; https://ink.library.smu.edu.sg/context/sis_research/article/10039/viewcontent/PIAS_av.pdf
• Institution: Singapore Management University

More vehicles are connecting to the Internet of Things (IoT), transforming Vehicle Ad hoc Networks (VANETs) into the Internet of Vehicles (IoV), providing a more environmentally friendly and safer driving experience. Vehicular announcement networks show promise in vehicular communication applications. However, two major issues arise when establishing such a system. Firstly, user privacy cannot be guaranteed when messages are forwarded anonymously, thus the reliability of these messages is in question. Secondly, users often lack interest in responding to announcements. To address these problems, we introduce a Blockchain-based incentive announcement system called PIAS. This system enables anonymous message commitment in a semi-trusted environment and encourages witnesses to respond to requests for traffic information. Additionally, PIAS uses blockchain accounts as identities to participate in the system with incentives, ensuring privacy in anonymous announcements. PIAS successfully protects the privacy of participants and motivates witnesses to respond to requests. Furthermore, our assessment of security and compatibility shows that PIAS can maintain privacy and incentivization while being compatible with both the Bitcoin and Ethereum blockchains. Further evaluation has confirmed the system's efficiency in terms of performance.