We consider the problem of security for unmanned aerial vehicle flight control systems. To provide a concrete setting, we consider the security problem in the context of a helicopter which is compromised by a malicious agent that distorts elevation measurements to the control loop. This is a particular example of the problem of the security of stochastic control systems under erroneous observation measurements caused by malicious sensors within the system. In order to secure the control system, we consider dynamic watermarking, where a private random excitation signal is superimposed onto the control input of the flight control system. An attack detector at the actuator can then check if the reported sensor measurements are appropriately correlated with the private random excitation signal. This is done via two specific statistical tests whose violation signifies an attack. We apply dynamic watermarking technique to a 2-rotor-based 3-DOF helicopter control system test-bed. We demonstrate through both simulation and experimental results the performance of the attack detector on two attack models: a stealth attack, and a random bias injection attack.

We address the problem of security of stochastic control systems when observation measurements used to close the control loop may be erroneous, due to a malicious adversary who has intercepted the associated sensors or the communication network. We show how the method of dynamic watermarking can be employed to secure such a system. This is a method of defense based on stochastic considerations, relying on the inability of the attacker to separate the ambient noise present in the system from a deliberatively superimposed random watermark. We present the results of experiments against several attacks, and show the capability of this method to detect attacks in all the tested cases. The experiments are conducted on a prototypical process control system consisting of two coupled water tanks.

We introduce our comprehensive end-to-end cyber-secure and resilient defense framework through a general-purpose pro-active defense methodology called “Dynamic Watermarking (DW)” primarily focused on enhancing cyber-security, operational safety, and system resilience of networked Cyber-Physical Energy Systems (CPES). Especially, under unpredictable adversarial operational conditions in which networked sensor measurements are deliberately manipulated by malicious attackers. Our cyber-secure and resilient defense framework integrates three essential layers of security: (1) Detection layer (DETECT), (2) Localization layer (LOCALIZE), and (3) Mitigation layer (MITIGATE). The resiliency of our Dynamic Watermarking (DW)-based defense framework is tested and demonstrated experimentally with several potential attack scenarios on both a laboratory-scale grid-connected multi-inverter solar photovoltaic (PV) energy distribution system and real-world sensor measurements captured by CenterPoint Energy’s solar farms. Through integration of three essential layers of security (DETECT, LOCALIZE, and MITIGATE), our comprehensive end-to-end cyber-secure and resilient defense framework enhances cyber-security and resilience for the networked Cyber-Physical Energy Systems (CPES) against a wide range of arbitrary cyber-physical attacks. This study contributes to enhance cyber-security, operational safety, and system resilience for emerging renewable-rich energy distribution systems.