a b s t r a c tCyber-secure networked control is modeled, analyzed, and experimentally illustrated in this paper. An attack space defined by the adversary's model knowledge, disclosure, and disruption resources is introduced. Adversaries constrained by these resources are modeled for a networked control system architecture. It is shown that attack scenarios corresponding to denial-of-service, replay, zero-dynamics, and bias injection attacks on linear time-invariant systems can be analyzed using this framework. Furthermore, the attack policy for each scenario is described and the attack's impact is characterized using the concept of safe sets. An experimental setup based on a quadruple-tank process controlled over a wireless network is used to illustrate the attack scenarios, their consequences, and potential countermeasures.

The alternating direction method of multipliers (ADMM) has emerged as a powerful technique for largescale structured optimization. Despite many recent results on the convergence properties of ADMM, a quantitative characterization of the impact of the algorithm parameters on the convergence times of the method is still lacking.In this paper we find the optimal algorithm parameters that minimize the convergence factor of the ADMM iterates in the context of ℓ2-regularized minimization and constrained quadratic programming. Numerical examples show that our parameter selection rules significantly outperform existing alternatives in the literature.

In this paper the existence of unknown input observers for networks of interconnected second-order linear time invariant systems is studied. Two classes of distributed control systems of large practical relevance are considered. It is proved that for these systems one can construct a bank of unknown input observers, and use them to detect and isolate faults in the network. The result presents a distributed implementation. In particular, by exploiting the system structure, this work provides further insight into the design of UIO for networked systems. Moreover, the importance of certain network measurements is shown. Infeasibility results with respect to available measurements and faults are also provided, as well as methods to remove faulty agents from the network. Applications to power networks and robotic formations are presented. It is shown how the developed methodology apply to a power network described by the swing equation with a faulty bus. For a multi-robot system, it is illustrated how a faulty robot can be detected and removed.

Abstract-In this paper the problem of revealing stealthy data-injection attacks on control systems is addressed. In particular we consider the scenario where the attacker performs zero-dynamics attacks on the system. First, we characterize and analyze the stealthiness properties of these attacks for linear time-invariant systems. Then we tackle the problem of detecting such attacks by modifying the system's structure. Our results provide necessary and sufficient conditions that the modifications should satisfy in order to detect the zerodynamics attacks. The results and proposed detection methods are illustrated through numerical examples.

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The problem of localization and circumnavigation of a slowly moving target with unknown speed has been considered. The agent only knows its own position with respect to its initial frame, and the bearing angle to the target in that frame. We propose an estimator to localize the target and a control law that forces the agent to move on a circular trajectory around the target such that both the estimator and the control system are exponentially stable. We consider two different cases where the agent's speed is constant and variable. The performance of the proposed algorithm is verified through simulations.

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