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Reliable data fusion in wireless sensor networks under Byzantine attacks

机译:拜占庭式攻击下无线传感器网络中的可靠数据融合

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In this paper, Byzantine attacks in wireless sensor networks with mobile access (SENMA) points is considered, where a portion of the active sensors are compromised to send false information. One effective method to combat with Byzantine attacks is the q-out-of-m scheme, where the sensing decision is based on q sensing reports out of m polled nodes. In this paper, first, by exploiting the approximately linear relationship between the scheme parameters and the network size, we propose a simplified q-out-of-m scheme which can greatly reduce the computational complexity, and at the same time keeping good performance. We show that for a fixed percentage of malicious sensors, the detection accuracy of the simplified q-out-of-m scheme increases almost exponentially as the network size increases. Second, we propose a simple but effective method to detect the malicious sensors before decision making. The performance of the proposed approach is evaluated under both static and dynamic attacking strategies. It is observed that with the pre-detection procedure, the performance of the q-out-of-m scheme can be improved significantly under various attacking strategies. Simulation results are provided to illustrate the effectiveness of the proposed approaches.
机译:在本文中,考虑了具有移动访问(SENMA)点的无线传感器网络中的拜占庭式攻击,其中一部分活动传感器受到攻击以发送虚假信息。一种应对拜占庭式攻击的有效方法是q-out-of-m方案,其中的感知决策基于m个轮询节点中的q个感知报告。在本文中,首先,通过利用方案参数与网络规模之间的近似线性关系,我们提出了一种简化的q-out-of-m方案,该方案可以大大降低计算复杂度,同时保持良好的性能。我们表明,对于固定百分比的恶意传感器,简化的q-out-of-m方案的检测精度会随着网络规模的增加而呈指数增长。其次,我们提出了一种简单但有效的方法,可以在决策前检测恶意传感器。在静态和动态攻击策略下都评估了所提出方法的性能。可以看出,通过预检测程序,在各种攻击策略下,q-out-of-m方案的性能可以得到显着改善。仿真结果表明了所提出方法的有效性。

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