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Context-adaptive detection of insider attacks in VANET information dissemination schemes

机译:VANET信息传播方案中针对内部攻击的上下文自适应检测

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Information dissemination is one of the most-discussed applications for vehicular ad hoc networks (VANETs) and other ad hoc networks. To provide dependability for applications, information dissemination must be resilient against different kinds of attacks. Especially insider attackers, which may create valid messages that cannot easily be detected using cryptographic signatures alone, pose a viable threat to information dependability. Many proposals in existing work offer solutions to detect individual attack patterns using data consistency checks and other means. We propose a generic framework that can integrate a wide range of existing detection mechanisms, allows to combine their outputs to improve attack detection, and enables mechanism adaptation based on current attack likelihood. We employ subjective logic opinions, which enable flexible security mechanism output representation, and which we extend to support continuing operation in dynamic networks, such as VANETs. Simulation results show that our framework improves detection accuracy compared to applying individual mechanisms.
机译:信息传播是车辆自组织网络(VANET)和其他自组织网络中讨论最多的应用之一。为了提供应用程序的可靠性,信息传播必须具有抵御各种攻击的能力。特别是内部攻击者可能会创建仅使用加密签名无法轻易检测到的有效消息,这对信息可靠性构成了切实威胁。现有工作中的许多建议提供了使用数据一致性检查和其他手段来检测单个攻击模式的解决方案。我们提出了一个通用框架,该框架可以集成广泛的现有检测机制,允许组合它们的输出以改进攻击检测,并能够根据当前攻击可能性对机制进行调整。我们采用主观逻辑意见,以实现灵活的安全机制输出表示,并扩展以支持诸如VANET之类的动态网络中的连续操作。仿真结果表明,与应用单个机制相比,我们的框架提高了检测精度。

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