A Novel Fuzzy Trust-Based Secure Vehicular Data Forwarding Scheme Using Incentive Consensus

Tieming Chen, Zechen Liu, Yinglong Li, Tinghao Chen, Qingyan Jiang, Jiahui Li

Abstract: Secure and efficient data forwarding is the basic infrastructure for edge services in vehicular ad hoc networks (VANETs). Existing vehicular data transmission methods such as multi-criteria decision-making usually have problems such as complex computation and high communication costs, as well as privacy leakage. To this end, a novel fuzzy trust-based VANET data forwarding scheme using incentive consensus is proposed. To begin with, the fuzzy trust of each Candidate Relay Vehicle (CRV) is obtained based on both the historical forwarding records and the real-time forwarding capabilities of CRVs to achieve privacy protection. Then an incentive consensus mechanism is devised, in which forwarding records uploading and incentive consensus are performed at roadside units, ensuring the uploaded records are trustworthy and tamper-proof. Furthermore, incentive rules are designed to attract more ‘fuzzy-high’ trust vehicles to participate in data forwarding. The proposed scheme was evaluated using both the vehicular network simulator VANETSIM and the Hyperledger Fabric blockchain platform. Experimental results show that our scheme outperforms the state-of-the-art methods in terms of packet loss rate and real-time performance.