Enhancing Trust Management System for Connected Autonomous Vehicles Using Machine Learning Methods: A Survey

TL;DR

This survey reviews how machine learning enhances trust management systems in connected autonomous vehicles, proposing a novel three-layer framework and categorizing recent research based on traffic scenarios and objectives.

Contribution

It introduces a new three-layer ML-based trust management framework for CAVs and provides a comprehensive taxonomy and categorization of recent studies.

Findings

Proposes a three-layer ML-based TMS framework for CAVs

Classifies recent research based on traffic scenarios and objectives

Highlights open issues and future research directions

Abstract

Connected Autonomous Vehicles (CAVs) operate in dynamic, open, and multi-domain networks, rendering them vulnerable to various threats. Trust Management Systems (TMS) systematically organize essential steps in the trust mechanism, identifying malicious nodes against internal threats and external threats, as well as ensuring reliable decision-making for more cooperative tasks. Recent advances in machine learning (ML) offer significant potential to enhance TMS, especially for the strict requirements of CAVs, such as CAV nodes moving at varying speeds, and opportunistic and intermittent network behavior. Those features distinguish ML-based TMS from social networks, static IoT, and Social IoT. This survey proposes a novel three-layer ML-based TMS framework for CAVs in the vehicle-road-cloud integration system, i.e., trust data layer, trust calculation layer and trust incentive layer. A six-dimensional taxonomy of objectives is proposed. Furthermore, the principles of ML methods for each module in each layer are analyzed. Then, recent studies are categorized based on traffic scenarios that are against the proposed objectives. Finally, future directions are suggested, addressing the open issues and meeting the research trend. We maintain an active repository that contains up-to-date literature and open-source projects at https://github.com/octoberzzzzz/ML-based-TMS-CAV-Survey.