Toward Cyber-Secure and Resilient Networked Control Systems
Abstract: Resilience is the ability to maintain acceptable levels of operation in the presence of abnormal conditions. It is an essential property in industrial control systems, which are the backbone of several critical infrastructures. The trend towards using pervasive information technology systems, such as the Internet, results in control systems becoming increasingly vulnerable to cyber threats. Traditional cyber security does not consider the interdependencies between the physical components and the cyber systems. On the other hand, control-theoretic approaches typically deal with independent disturbances and faults, thus they are not tailored to handle cyber threats. Theory and tools to analyze and build control system resilience are, therefore, lacking and in need to be developed. This thesis contributes towards a framework for analyzing and building resilient control systems.First, a conceptual model for networked control systems with malicious adversaries is introduced. In this model, the adversary aims at disrupting the system behavior while remaining undetected by an anomaly detector The adversary is constrained in terms of the available model knowledge, disclosure resources, and disruption capabilities. These resources may correspond to the anomaly detector’s algorithm, sniffers of private data, and spoofers of control commands, respectively.Second, we address security and resilience under the perspective of risk management, where the notion of risk is defined in terms of a threat’s scenario, impact, and likelihood. Quantitative tools to analyze risk are proposed. They take into account both the likelihood and impact of threats. Attack scenarios with high impact are identified using the proposed tools, e.g., zero-dynamics attacks are analyzed in detail. The problem of revealing attacks is also addressed. Their stealthiness is characterized, and how to detect them by modifying the system’s structure is also described.As our third contribution, we propose distributed fault detection and isolation schemes to detect physical and cyber threats on interconnected second-order linear systems. A distributed scheme based on unknown input observers is designed to jointly detect and isolate threats that may occur on the network edges or nodes. Additionally, we propose a distributed scheme based on local models and measurements that is resilient to changes outside the local subsystem. The complexity of the proposed methods is decreased by reducing the number of monitoring nodes and by characterizing the minimum amount of model information and measurements needed to achieve fault detection and isolation.Finally, we tackle the problem of distributed reconfiguration under sensor and actuator faults. In particular, we consider a control system with redundant sensors and actuators cooperating to recover from the removal of individual nodes. The proposed scheme minimizes a quadratic cost while satisfying a model-matching condition, which maintains the nominal closed-loop behavior after faults. Stability of the closed-loop system under the proposed scheme is analyzed.
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