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Enabling Seamless Data Security, Consensus, and Trading in Vehicular Networks (2401.13630v1)

Published 24 Jan 2024 in cs.DC

Abstract: Cooperative driving is an emerging paradigm to enhance the safety and efficiency of autonomous vehicles. To ensure successful cooperation, road users must reach a consensus for making collective decisions, while recording vehicular data to analyze and address failures related to such agreements. This data has the potential to provide valuable insights into various vehicular events, while also potentially improving accountability measures. Furthermore, vehicles may benefit from the ability to negotiate and trade services among themselves, adding value to the cooperative driving framework. However, the majority of proposed systems aiming to ensure data security, consensus, or service trading, lack efficient and thoroughly validated mechanisms that consider the distinctive characteristics of vehicular networks. These limitations are amplified by a dependency on the centralized support provided by the infrastructure. Furthermore, corresponding mechanisms must diligently address security concerns, especially regarding potential malicious or misbehaving nodes, while also considering inherent constraints of the wireless medium. We introduce the Verifiable Event Extension (VEE), an applicational extension designed for Intelligent Transportation System (ITS) messages. The VEE operates seamlessly with any existing standardized vehicular communications protocol, addressing crucial aspects of data security, consensus, and trading with minimal overhead. To achieve this, we employ blockchain techniques, Byzantine fault tolerance (BFT) consensus protocols, and cryptocurrency-based mechanics. To assess our proposal's feasibility and lightweight nature, we employed a hardware-in-the-loop setup for analysis. Experimental results demonstrate the viability and efficiency of the VEE extension in overcoming the challenges posed by the distributed and opportunistic nature of wireless vehicular communications.

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