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Defending Wireless Sensor Networks against Adversarial Localization

机译:防御无线传感器网络对抗对抗性本地化

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In this paper, we study the issue of defending against adversarial localization in wireless sensor networks. Adversarial localization refers to attacks where an adversary attempts to disclose physical locations of sensors in the network. The adversary accomplishes this by physically moving in the network while eavesdropping on communication messages exchanged by sensors, and measuring raw physical properties of messages like Angle of Arrival, Signal Strength of the detected signal. In this paper, we aim to defend sensor networks against such kinds of adversarial localization. The core challenge comes from the sensors performing two conflicting objectives simultaneously: localize the adversary, and hide from the adversary. The principle of our approach and the subsequent defense protocol is to allow sensors intelligently predict their own importance as a measure of these two conflicting requirements. Only a few important sensors will participate in any message exchanges. This ensures high degree of adversary localization, while also protecting location privacy of many sensors. Extensive simulations are conducted to demonstrate the performance of our protocol.
机译:在本文中,我们研究了在无线传感器网络中防御对抗性本地化的问题。对抗性本地化是指攻击者试图揭露网络中传感器的物理位置的攻击。攻击者通过窃听传感器交换的通信消息并在网络中进行物理移动,并测量消息的原始物理属性(例如到达角度,检测到的信号的信号强度)来实现此目的。在本文中,我们旨在针对此类对抗性定位防御传感器网络。核心挑战来自传感器同时执行两个相互矛盾的目标:定位对手并躲避对手。我们的方法和随后的防御协议的原理是允许传感器智能地预测其自身的重要性,以衡量这两个相互矛盾的要求。只有少数重要的传感器会参与任何消息交换。这确保了高度的对手定位,同时还保护了许多传感器的位置隐私。进行了广泛的仿真,以证明我们协议的性能。

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