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Survey on Misbehavior Detection in Cooperative Intelligent Transportation Systems

机译:协同智能交通系统行为不当检测研究

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Cooperative intelligent transportation systems (cITS) are a promising technology to enhance driving safety and efficiency. Vehicles communicate wirelessly with other vehicles and infrastructure, thereby creating a highly dynamic and heterogeneously managed ad-hoc network. It is these network properties that make it a challenging task to protect integrity of the data and guarantee its correctness. A major component is the problem that traditional security mechanisms like public key infrastructure (PKI)-based asymmetric cryptography only exclude outsider attackers that do not possess key material. However, because attackers can be insiders within the network (i.e., possess valid key material), this approach cannot detect all possible attacks. In this survey, we present misbehavior detection mechanisms that can detect such insider attacks based on attacker behavior and information analysis. In contrast to well-known intrusion detection for classical IT systems, these misbehavior detection mechanisms analyze information semantics to detect attacks, which aligns better with highly application-tailored communication protocols foreseen for cITS. In our survey, we provide an extensive introduction to the cITS ecosystem and discuss shortcomings of PKI-based security. We derive and discuss a classification for misbehavior detection mechanisms, provide an in-depth overview of seminal papers on the topic, and highlight open issues and possible future research trends.
机译:协作式智能交通系统(cITS)是提高驾驶安全性和效率的有前途的技术。车辆与其他车辆和基础设施进行无线通信,从而创建了高度动态且异构管理的自组织网络。正是这些网络属性使保护数据的完整性并确保其正确性成为一项艰巨的任务。一个主要的组成部分是这样的问题:传统的安全机制(如基于公共密钥基础结构(PKI)的非对称加密)仅排除了不拥有密钥材料的外部攻击者。但是,由于攻击者可能是网络内部的人(即拥有有效的密钥材料),因此这种方法无法检测到所有可能的攻击。在本次调查中,我们提出了不良行为检测机制,可以基于攻击者的行为和信息分析来检测此类内部攻击。与经典IT系统中众所周知的入侵检测相比,这些不当行为检测机制分析信息语义来检测攻击,这与针对cITS预见的高度应用定制的通信协议更好地吻合。在我们的调查中,我们提供了对cITS生态系统的广泛介绍,并讨论了基于PKI的安全性的缺点。我们推导并讨论了不良行为检测机制的分类,提供了关于该主题的开创性论文的深入概述,并突出了未解决的问题和可能的未来研究趋势。

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