Secure Distributed Control Methodologies with Built-in Defense in Distributed Networked Control Systems.

ZENG, WENTE. Secure Distributed Control Methodologies with Built-in Defense in Distributed Networked Control Systems. (Under the direction of Dr. Mo-Yuen Chow.) Distributed Networked Control Systems (D-NCS) are spatially distributed systems that integrate distributed sensors, actuators, and computing processors over a communication network for a vast amount of applications, such as electrical power systems and transportation systems. While most D-NCS have been safe in the past, they are increasingly more vulnerable to malicious cyber attacks and malwares with the rapid advancements and uses with networking, embedded systems, wireless communication technologies, and novel control strategies. In particular, more and more distributed control algorithms are being used in D-NCS because of their flexibility, robustness, computation, and communication features. These algorithms, however, increase the vulnerability of D-NCS to malicious cyber attacks. Thus, there is an urgent growing need to protect control algorithms from malicious cyber attacks in D-NCS. This thesis considers the fundamental task of reaching an agreement (i.e., consensus) among a group of agents via secure distributed computations in D-NCS and discusses the problem of designing secure distributed control methodologies that are capable of performing secure distributed computations in the presence of misbehaving agents. First, we develop the mathematical models of D-NCS and misbehaving agents in the network, and we explore the vulnerabilities of conventional linear consensus algorithms. Second, we propose a reputationbased secure distributed control algorithm with built-in defense mechanism for leaderfollower consensus network. It includes four phases (detection, mitigation, identification, and update) into the control process in a distributed manner and is able to achieve an accurate consensus computation in the presence of misbehaving agents in D-NCS. Third, we extend the proposed algorithm to the leaderless consensus network by introducing and adding two recovery schemes (rollback recovery and excitation recovery) into the current secure distributed control framework to guarantee the accurate convergence of the well-behaving agents in D-NCS. At each phase, every agent only uses local and one-hop neighbors’ information to identify and isolate the misbehaving agents, and even compensate their effect to the system. Fourth, we develop a trade-off model and corresponding quantitative metrics to address the performance and security trade-off problem of D-NCS. A paradigm of multiagent trade-off optimization based on the Coevolutionary Genetic Algorithm (CGA) is proposed to optimize the trade-off between system real-time performance and security levels. Finally, in order to analyze the performance of our theoretical design on a real-world problem, we examine and validate the effectiveness of the proposed techniques in several illustrative case studies through both simulations and experiments. © Copyright 2013 Wente Zeng All Rights Reserved Secure Distributed Control Methodologies with Built-in Defense in Distributed Networked Control Systems