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Distributed Robust Filtering for Wireless Sensor Networks with Markov Switching Topologies and Deception Attacks

机译：具有马尔可夫开关拓扑和欺骗攻击的无线传感器网络分布式鲁棒滤波

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摘要

This paper is concerned with the distributed full- and reduced-order - state estimation issue for a class of discrete time-invariant systems subjected to both randomly occurring switching topologies and deception attacks over wireless sensor networks. Firstly, a switching topology model is proposed which uses homogeneous Markov chain to reflect the change of filtering networks communication modes. Then, the sector-bound deception attacks among the communication channels are taken into consideration, which could better characterize the filtering network communication security. Additionally, a random variable obeying the Bernoulli distribution is used to describe the phenomenon of the randomly occurring deception attacks. Furthermore, through an adjustable parameter , we can obtain full- and reduced-order - state estimator over sensor networks, respectively. Sufficient conditions are established for the solvability of the addressed switching topology-dependent distributed filtering design in terms of certain convex optimization problem. The purpose of solving the problem is to design a distributed full- and reduced-order filter such that, in the presence of deception attacks, stochastic external interference and switching topologies, the resulting filtering dynamic system is exponentially mean-square stable with prescribed - performance index. Finally, a simulation example is provided to show the effectiveness and flexibility of the designed approach.
机译：本文涉及一类离散时不变系统的分布式全状态和降阶状态估计问题，该系统同时受到随机发生的切换拓扑和无线传感器网络的欺骗攻击的影响。首先，提出了一种交换拓扑模型，该模型使用齐次马尔可夫链来反映滤波网络通信模式的变化。然后，考虑通信通道之间的扇区绑定欺骗攻击，可以更好地表征过滤网络通信的安全性。另外，服从伯努利分布的随机变量用于描述随机发生的欺骗攻击的现象。此外，通过可调参数，我们可以分别通过传感器网络获得全阶和降阶状态估计器。就某些凸优化问题而言，为所解决的与开关拓扑相关的分布式滤波设计的可解性建立了充分条件。解决该问题的目的是设计一个分布式的全阶和降阶滤波器，以便在存在欺骗攻击，随机外部干扰和切换拓扑的情况下，所得的滤波动态系统具有规定性能的指数均方稳定指数。最后，提供了一个仿真示例来说明所设计方法的有效性和灵活性。

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