We consider the distributed $H_\infty$ estimation problem with an additional requirement of resilience to biasing attacks. An attack scenario is considered, where an adversary misappropriates some of the observer nodes and injects biasing signals into observer dynamics. This paper proposes a procedure for the derivation of a distributed observer, which endows each node with an attack detector, which also functions as an attack compensating feedback controller for the main observer. Connecting these controlled observers into a network results in a distributed observer whose nodes produce unbiased robust estimates of the plant. We show that the gains for each controlled observer in the network can be computed in a decentralized fashion, thus reducing vulnerability of the network.

中文翻译：

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分散式 $ H_ \ infty $ 抵御偏见攻击的估算

我们考虑分布式 $ H_ \ infty $估计问题，另外还需要具有抵抗偏见攻击的弹性。考虑一种攻击方案，在此方案中，敌方挪用了一些观察者节点，并将偏见信号注入了观察者动态。本文提出了一种分布式观察者的推导过程，该过程为每个节点赋予了攻击检测器，该检测器还可以作为主要观察者的攻击补偿反馈控制器。将这些受控观察者连接到网络中后，将得到一个分布式观察者，其节点可对工厂进行无偏健壮的估计。我们表明，可以以分散方式计算网络中每个受控观察者的收益，从而减少网络的脆弱性。