Mitigating Sensor Attacks Against Industrial Control Systems

Abstract

This paper describes how to design and implement a mechanism that helps to mitigate sensor attacks on industrial control systems. The proposed architecture is based on concepts from fault-tolerant control techniques. This short note explains how a Kalman filter can be used simultaneously with optimal disturbance decoupling observers to improve the performance of the mitigation mechanism for sensor attacks in cyber-physical control systems. Our proposal mitigates attacks by generating a signal that compensates the change provoked by the attacker, while at the same time reducing the number of false alarms. We demonstrate the effectiveness of our proposal using a three tanks control simulation.INDEX TERMS Cyber-physical control systems, industrial control systems, secure control, sensor attacks mitigation.LUIS F. CÓMBITA received the B.S. degree in electronics engineering from Universidad Distrital, Bogotá, Colombia, in 1992, and the M.S. degree in electrical engineering from the Universidad de los Andes, Bogotá, Colombia, in 2002, where he is currently pursuing the Ph.D. degree.He joined the Engineering Faculty, Universidad Distrital Francisco José de Caldas, Bogotá, as an Auxiliar Professor, in 1997, where he is currently an Assistant Professor. His current research interests include cyber-physical systems security, modelling and simulation of dynamical systems, and industrial control systems.

On the Stability of Cyber-Physical Control Systems With Sensor Multiplicative Attacks

“…which needs to be solved for , γ and P and, therefore, it is not an LMI. Finally, applying the Schur complement to each of the principal diagonal elements and defining α −1 = ε γ 2 , the problem of finding the upper limit for the attack in order the complete closed-loop system (controller together with observer) remains stable can be formulated as (20). If we only apply the Schur complement to the term −P + ε −1 P D D P in (32), the problem can be formulated as (21), with β = ε γ 2 .…”

“…The effect on the tracking closed-loop control systems stability of these two types of attacks is then analyzed and the vulnerability level of each sensor is quantified. We also use the attack detection, isolation, and mitigation mechanisms described in [20] to see if the considered attacks can be mitigated, finding that once the attacker succeeds in making the system unstable, secure state estimation and, therefore, the mitigation of the sensor attack cannot be achieved. We use some tools from robust control theory to formulate two equivalent optimization problems with LMI constraints, which allows us to find a conservative limit on the gain of each sensor of the system to determine which of the system outputs is more vulnerable to multiplicative attacks.…”

Cyber-Resilience Evaluation of Cyber-Physical Systems

“…In addition, sensor resilience can be improved using software approaches that do not require to add extra hardware devices. For example, the techniques proposed in [12], [5], [6] and [25] provide resilient state estimation and reconstruction in the presence of integrity attacks.…”

On the performance metrics for cyber-physical attack detection in smart grid

“…The protection of communication protocols, asset management, physical infrastructures, and controlled processes will come under the security of the SCADA system that is the most important element of the smart grid, and these cannot be handled the same as IT system contemporaries. Some of the key components are supporting software such as Human Machine Interface (HMI), Distributed Control Systems (DCS), Programmable Logical Controllers (PLC), Remote Terminal Units (RTU), network equipment, servers, and computers (Co ´mbita et al 2019, Pang et al 2020, Sun et al 2020, Elnour et al 2020). Hence, it is essential to protect the system against attacks and secure communication.…”