The comprehensive integration of instrumentation, communication, and control into physical systems has led to the study of Cyber-Physical Systems (CPS), a field that has recently garnered increased attention. A key concern that is ubiquitous in CPS is a need to ensure security in the face of cyber attacks. In this paper, we carry out a survey of systems and control methods that have been proposed for the security of CPS. We classify these methods into three categories based on the type of defense proposed against the cyberattacks: prevention, resilience, and detection & isolation. A unified threat assessment metric is proposed in order to evaluate how CPS security is achieved in each of these three cases. Also surveyed are risk assessment tools and the effect of network topology on CPS security. An emphasis has been placed on power and transportation applications in the overall survey. Index Terms-cyber-physical systems, resilient control I. INTRODUCTION Motivated by concerns about sustainability, efficiency, and resiliency, several sectors including energy, transportation, water, and healthcare systems have witnessed significant advances in instrumentation, monitoring, and automation over the past decade. The resulting integration of information, communication, and computation with physically engineered systems demands a detailed investigation into the analysis and synthesis of Cyber-Physical Systems (CPS) so as to realize the desired performance metrics of efficiency, sustainability, and safety. The extensive and intricate presence of cyber components also introduces a vulnerability of unwanted access to these systems. The available communication technologies, referred to as SCADA (Supervisory Control and Data Acquisition), are witnessing significant advances, triggering a shift from protected, closed, and wired networks to open and wireless networks which, as a side effect, are more vulnerable to outside interference.

We study the problem of resilient consensus of sampled-data multi-agent networks with double-integrator dynamics. The term resilient points to algorithms considering the presence of attacks by faulty/malicious agents in the network. Each normal agent updates its state based on a predetermined control law using its neighbors' information which may be delayed while misbehaving agents make updates arbitrarily and might threaten the consensus within the network. Assuming that the maximum number of malicious agents in the system is known, we focus on algorithms where each normal agent ignores large and small position values among its neighbors to avoid being influenced by malicious agents. The malicious agents are assumed to be omniscient in that they know the updating times and delays and can collude with each other. We deal with both synchronous and partially asynchronous cases with delayed information and derive topological conditions in terms of graph robustness.

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Abstract-We consider the problem of multi-agent consensus where some agents are subject to faults/attacks and might make updates arbitrarily. The network consists of agents taking integervalued (i.e., quantized) states under directed communication links. The goal of the healthy normal agents is to form consensus in their state values, which may be disturbed by the non-normal, malicious agents. We develop update schemes to be equipped by the normal agents whose interactions are asynchronous and subject to non-uniform and time-varying time delays. In particular, we employ a variant of the so-called mean subsequence reduced (MSR) algorithms, which have been long studied in computer science, where each normal agent ignores extreme values from its neighbors. We solve the resilient quantized consensus problems in the presence of totally/locally bounded adversarial agents and provide necessary and sufficient conditions in terms of the connectivity notion of graph robustness. Furthermore, it will be shown that randomization is essential both in quantization and in the updating times when normal agents interact in an asynchronous manner. The results are examined through a numerical example.

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