The coming decades may see the large scale deployment of networked cyber-physical systems to address global needs in areas such as energy, water, healthcare, and transportation. However, as recent events have shown, such systems are vulnerable to cyber attacks. Being safety critical, their disruption or misbehavior can cause economic losses or injuries and loss of life. It is therefore important to secure such networked cyberphysical systems against attacks. In the absence of credible security guarantees, there will be resistance to the proliferation of cyber-physical systems, which are much needed to meet global needs in critical infrastructures and services.This paper addresses the problem of secure control of networked cyber-physical systems. This problem is different from the problem of securing the communication network, since cyberphysical systems at their very essence need sensors and actuators that interface with the physical plant, and malicious agents may tamper with sensors or actuators, as recent attacks have shown.We consider physical plants that are being controlled by multiple actuators and sensors communicating over a network, where some sensors could be "malicious," meaning that they may not report the measurements that they observe. We address a general technique by which the actuators can detect the actions of malicious sensors in the system, and disable closedloop control based on their information. This technique, called "watermarking," employs the technique of actuators injecting private excitation into the system which will reveal malicious tampering with signals. We show how such an active defense can be used to secure networked systems of sensors and actuators.

We propose an online framework to detect cyber attacks on Automatic Generation Control (AGC). A cyber attack detection algorithm is designed based on the approach of Dynamic Watermarking. The detection algorithm provides a theoretical guarantee of detection of cyber attacks launched by sophisticated attackers possessing extensive knowledge of the physical and statistical models of targeted power systems. The proposed framework is practically implementable, as it needs no hardware update on generation units. The efficacy of the proposed framework is validated in both four-area system and 140-bus system. His research interests include modeling and control of large-scale complex systems, smart grids application with renewable energy resources, and electricity markets.

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The transportation sector is on the threshold of a revolution as advances in real-time communication, real-time computing, and sensing technologies have brought to fruition the capability to build Transportation Cyber-Physical Systems (TCPS) such as self-driving cars, unmanned aerial vehicles, adaptive cruise control systems, truck platoons, and so on. While there are many benefits that TCPSs have to offer, a major challenge that needs to be addressed to enable their proliferation is their vulnerability to cyber attacks. In this article, we demonstrate, using laboratory prototypes of TCPSs, how the approach of Dynamic Watermarking can secure them from arbitrary sensor attacks. Specifically, we consider two TCPSs of topical interest: (i) an adaptive cruise control system and (ii) a system of self-driving vehicles tracking given trajectories. In each of these systems, we first show how cyber attacks on sensors can compromise safety and cause collisions between vehicles in spite of the presence of a collision avoidance module in the system. We then apply the approach of Dynamic Watermarking and demonstrate that it detects attacks with “low” delay. Once an attack is detected, the controller can take appropriate control actions to prevent collisions, thereby guaranteeing safety in the sense of collision freedom.

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