Reputation Evaluation Scheme Based on PUF and Blockchain With Channel Congestion Mitigation in the Internet of Vehicles
The Internet of Vehicles (IoV) can significantly enhance the efficiency of message dissemination on roads, playing a vital role in reducing traffic accidents. Due to the limited computational resources of individual vehicles, they must share observed data with roadside unit (RSU) and other vehicles to handle computational tasks that allow for some delay. However, the data provided by vehicles may not always be reliable, and false information can have severe consequences. Additionally, excessive data sharing can lead to channel congestion, preventing critical messages from being disseminated in a timely manner. To address these challenges, we propose a channel congestion mitigation and reputation evaluation scheme based on physically unclonable function (PUF) and blockchain technology. First, we generate a unique ID for each vehicle using the PUF function, and then introduce a digital certificate to ensure that messages originating from a vehicle can be traced back to their source. The vehicle’s identity is verified before any communication with the RSU. Second, we utilize a cuckoo filter to prevent the redundant sharing of identical reports for vehicle parameters. Both vehicles and RSUs can check their local filters to verify whether a data report has already been shared. Moreover, we introduce a specialized buffer structure in RSUs to eliminate false information received during communication and identify potentially malicious vehicles. Finally, we conducted experiments to verify the efficiency and accuracy of our scheme, demonstrating its feasibility and effectiveness.
Authors
- Bo Zhang (ORCID: https://orcid.org/0000-0003-4227-1741)
- Xiancheng Feng
Institutions
- University of Jinan (CN)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2025-02-05
- DOI
- https://doi.org/10.1109/jiot.2025.3538984
- Citations
- 3
- Primary Topic
- Advanced Computing and Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 18.53