网络化自主系统中基于AI/ML的入侵与异常行为检测综述：技术、挑战与机遇
A Survey on AI/ML-Driven Intrusion and Misbehavior Detection in Networked Autonomous Systems: Techniques, Challenges and Opportunities
AI总结：
本综述深入分析AI/ML驱动的入侵与异常行为检测系统，建立基线评估指标，指出当前文献空白，并为车载网络应用提出解决方案指南，以促进其实际部署。
摘要：
基于人工智能/机器学习（AI/ML）的入侵检测系统（IDSs）和异常行为检测系统（MDSs）在识别网络化自主系统网络流量中的异常方面展现出巨大潜力。尽管已有大量研究工作，但此类系统在实际中的部署仍然有限。虽然自主系统的安全关键性以及基于学习的技术易受对抗性攻击是潜在原因之一，但缺乏客观评估和可行性评估指标是这些系统在实际场景中采用有限的关键原因之一。本综述旨在通过深入分析基于AI/ML的IDSs/MDSs并建立与网络化自主系统相关的基线指标来解决上述局限性。此外，本工作全面调研了该领域的最新研究，重点指出了当前文献中的评估指标和空白。它还提出了我们从所调研论文的分析中得出的关键发现，并为适用于车载网络应用的基于AI/ML的IDS/MDS解决方案方法提出了指导方针。我们的工作为研究人员和从业者提供了评估基于AI/ML的IDS/MDS技术在实际场景中可行性所需的工具，旨在促进这些技术在新兴自主车载系统中的实际采用。
英文摘要：
AI/ML-based intrusion detection systems (IDSs) and misbehavior detection systems (MDSs) have shown great potential in identifying anomalies in the network traffic of networked autonomous systems. Despite the vast research efforts, practical deployments of such systems in the real world have been limited. Although the safety-critical nature of autonomous systems and the vulnerability of learning-based techniques to adversarial attacks are among the potential reasons, the lack of objective evaluation and feasibility assessment metrics is one key reason behind the limited adoption of these systems in practical settings. This survey aims to address the aforementioned limitation by presenting an in-depth analysis of AI/ML-based IDSs/MDSs and establishing baseline metrics relevant to networked autonomous systems. Furthermore, this work thoroughly surveys recent studies in this domain, highlighting the evaluation metrics and gaps in the current literature. It also presents key findings derived from our analysis of the surveyed papers and proposes guidelines for providing AI/ML-based IDS/MDS solution approaches suitable for vehicular network applications. Our work provides researchers and practitioners with the needed tools to evaluate the feasibility of AI/ML-based IDS/MDS techniques in real-world settings, with the aim of facilitating the practical adoption of such techniques in emerging autonomous vehicular systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
