A Framework for Consistent and Repeatable Controller Area Network IDS Evaluation
A Framework for Consistent and Repeatable Controller Area Network IDS Evaluation
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DOI：
10.14722/autosec.2022.23031
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Paul Agbaje;A. Anjum;Arkajyoti Mitra;Gedare Bloom;Habeeb Olufowobi
中科院分区：
文献类型：
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作者：
Paul Agbaje;A. Anjum;Arkajyoti Mitra;Gedare Bloom;Habeeb Olufowobi
-汽车攻击的形势持续增长，控制器区域网络（CAN）中的漏洞使车辆暴露于网络物理风险和攻击中，可能危及乘客和行人的安全。针对CAN的入侵检测系统（IDS）已成为缓解这些风险的关键方法，但缺乏统一的方法来比较所提出的入侵检测技术。在本文中，我们提出了一个框架，用于比较最先进的CAN总线ids的性能分析，以提供一致的方法来评估和评估所提出的方法。该框架依赖于以前发布的数据集，这些数据集包括从真实车辆CAN总线记录的消息日志，以及传统的分类器性能指标，以减少在比较来自不同来源的IDS方法时出现的差异。
—The landscape of automotive vehicle attack surfaces continues to grow, and vulnerabilities in the controller area network (CAN) expose vehicles to cyber-physical risks and attacks that can endanger the safety of passengers and pedestrians. Intrusion detection systems (IDS) for CAN have emerged as a key mitigation approach for these risks, but uniform methods to compare proposed IDS techniques are lacking. In this paper, we present a framework for comparative performance analysis of state-of-the-art IDSs for CAN bus to provide a consistent methodology to evaluate and assess proposed approaches. This framework relies on previously published datasets comprising message logs recorded from a real vehicle CAN bus coupled with traditional classifier performance metrics to reduce the discrepancies that arise when comparing IDS approaches from disparate sources.