A Trustworthy Internet of Vehicles: The DAO to Safe, Secure, and Collaborative Autonomous Driving - Université Gustave Eiffel
Article Dans Une Revue IEEE Transactions on Intelligent Vehicles Année : 2023

A Trustworthy Internet of Vehicles: The DAO to Safe, Secure, and Collaborative Autonomous Driving

Résumé

The potential of the Internet of Vehicles (IoV) to reduce on-board system costs in autonomous vehicles through shared intelligence is considerable. However, it still faces significant challenges, including concerns over data breaches and privacy, inefficiencies and limited fault tolerance in centralized management, and the challenge of ensuring data accuracy. This letter marks the inaugural report from a series of IEEE Transactions on Intelligent Vehicles (TIV) Trustworthy IoV Workshops, which aim to address these issues. In these workshops, we explore the concept of a decentralized IoV (DeIoV), underpinned by decentralized autonomous organizations and operations (DAOs), to facilitate trustworthy interactions between vehicles and other entities. The proposed DeIoV is structured in two layers: the local DAO layer and the global DAO layer. This dual-layer architecture distinguishes between real-time and non-real-time decision-making tasks, aiding in their efficient completion. To ensure data security, integrity, and accuracy, we employ blockchain technology and smart contracts, which allow for mutual verification among adjacent members and utilize encryption algorithms. A reputation value-based voting mechanism for decision-making is also introduced, which helps prevent the monopolization of power through token-based systems, a common issue in traditional DAOs. Ultimately, we believe that DeIoV has the potential to create a trustworthy IoV ecosystem, contributing significantly to safe, secure, and collaborative autonomous driving.
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Dates et versions

hal-04401352 , version 1 (17-01-2024)

Identifiants

Citer

Jing Yang, Qinghua Ni, Guiyang Luo, Qi Cheng, Latifa Oukhellou, et al.. A Trustworthy Internet of Vehicles: The DAO to Safe, Secure, and Collaborative Autonomous Driving. IEEE Transactions on Intelligent Vehicles, 2023, 8 (12), pp.4678-4681. ⟨10.1109/TIV.2023.3337345⟩. ⟨hal-04401352⟩
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