科研之友
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摘要
The recent fast growth of the internet-of-vehicle (IoV) market has sparked interest in accurate positioning using time-difference-of-arrival (TDOA) schemes. However, the rapid development of the IoV networks has been challenged by a significant increase in malicious attacks that can drastically degrade the lo-calization performance. In this paper, we propose a blockchain-aided vehicular localization scheme as protection against malicious attacks. Specifically, a lightweight and robust trust evaluation process is de-veloped to identify malicious nodes by using target location estimates and node energy consumption behaviors. We provide a theoretical framework to characterize the impact of blockchain and computa-tional delays on TDOA-based localization. Furthermore, a tractable Cram e acute accent r-Rao lower bound (CRLB) is derived using stochastic geometry to quantify the localization performance with random network con-figurations. Simulation results demonstrate that the proposed scheme efficiently protects the localization system against various malicious attacks and accurately estimates the target position even under a high proportion of malicious nodes. The devised benchmark precisely measures the blockchain-aided TDOA-based localization performance in IoV networks and provides insights into localization optimization with-out lengthy and complicated simulations.
