LBDT: A Lightweight Blockchain-Based Data Trading Scheme in Internet of Vehicles Using Proof-of-Reputation

Weilin Chen, Wei Yang, Mingjun Xiao, Lide Xue, Shaowei Wang

Abstract: The exponential growth of data in the Internet of Vehicles (IoV) has created opportunities to improve traffic safety and efficiency through data trading. However, establishing trust among highly mobile and resource-constrained vehicles poses significant challenges for effective data trading in IoV. To address this issue, we propose a lightweight blockchain-based data trading scheme (LBDT), which ensures secure and efficient data trading in IoV. We introduce a proof-of-reputation (PoR) consensus mechanism to establish trustworthiness for data trading. Specifically, we use a progressive reputation mechainism to support the PoR consensus. LBDT utilizes a parallel-chain structure for the PoR consensus to minimize communication and storage costs while reducing transaction confirmation latency. Additionally, we adopt a double auction mechanism as an incentivizing strategy to encourage vehicle participation in data trading. We evaluate the performance of LBDT through extensive experiments. The experimental results demonstrate that LBDT is highly effective and secure, achieving a transaction latency of approximately 4 seconds. Moreover, LBDT successfully mitigates communication and storage overheads by over 90%, thus establishing its superiority over state-of-the-art solutions under comparable conditions.