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On the Impact of Localization Data in Wireless Sensor Networks with Malicious Nodes

机译:带有恶意节点的无线传感器网络中本地化数据的影响

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The knowledge of node positions is a core concept in any Wireless Sensor Network context. Several localization algorithms were devised, but secure localization of sensor nodes is still a challenging task to achieve with a high level of performance. In fact, location information might be the target of different kinds of malicious attacks and several secure localization approaches were proposed. In this paper we analyze the impact of false data in a secure localization algorithm, known as Verifiable Multilateration. We found that the strategy used to compute the positions of nodes might have an impact both on the computational effort needed to achieve acceptable measures and the precision of the detection of malicious nodes.
机译:在任何无线传感器网络环境中,节点位置的知识都是核心概念。设计了几种定位算法,但是传感器节点的安全定位仍然是一项具有较高性能的挑战性任务。实际上,位置信息可能是各种恶意攻击的目标,因此提出了几种安全的本地化方法。在本文中,我们分析了错误数据对安全定位算法(可验证多边验证)的影响。我们发现,用于计算节点位置的策略可能对实现可接受的措施所需的计算工作量以及恶意节点检测的精度都有影响。

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