Reinforcement learning based anti-jamming schedule in cyber-physical systems

In this paper, the security issue of cyber-physical systems is investigated, where the observation data is transmitted from a sensor to an estimator through wireless channels disturbed by an attacker. The failure of this data transmission occurs, when the sensor accesses the channel that happens to be attacked by the jammer. Since the system performance measured by the estimation error depends on whether the data transmission is a success, the problem of selecting the channel to alleviate the attack effect is studied. Moreover, the state of each channel is time-variant due to various factors, such as path loss and shadowing. Motivated by energy conservation, the problem of selecting the channel with the best state is also considered. With the help of cognitive radio technique, the sensor has the ability of selecting a sequence of channels dynamically. Based on this, the problem of selecting the channel is resolved by means of reinforcement learning to jointly avoid the attack and enjoy the channel with the best state. A corresponding algorithm is presented to obtain the sequence of channels for the sensor, and its effectiveness is proved analytically. Numerical simulations further verify the derived results

Bad Data Injection Attack and Defense in Electricity Market using Game Theory Study

Applications of cyber technologies improve the quality of monitoring and decision making in smart grid. These cyber technologies are vulnerable to malicious attacks, and compromising them can have serious technical and economical problems. This paper specifies the effect of compromising each measurement on the price of electricity, so that the attacker is able to change the prices in the desired direction (increasing or decreasing). Attacking and defending all measurements are impossible for the attacker and defender, respectively. This situation is modeled as a zero sum game between the attacker and defender. The game defines the proportion of times that the attacker and defender like to attack and defend different measurements, respectively. From the simulation results based on the PJM 5 Bus test system, we can show the effectiveness and properties of the studied game.Comment: To appear in IEEE Transactions on Smart Grid, Special Issue on Cyber, Physical, and System Security for Smart Gri

Bibliographical review on cyber attacks from a control oriented perspective

This paper presents a bibliographical review of definitions, classifications and applications concerning cyber attacks in networked control systems (NCSs) and cyber-physical systems (CPSs). This review tackles the topic from a control-oriented perspective, which is complementary to information or communication ones. After motivating the importance of developing new methods for attack detection and secure control, this review presents security objectives, attack modeling, and a characterization of considered attacks and threats presenting the detection mechanisms and remedial actions. In order to show the properties of each attack, as well as to provide some deeper insight into possible defense mechanisms, examples available in the literature are discussed. Finally, open research issues and paths are presented.Peer ReviewedPostprint (author's final draft

Co-design of Control and Scheduling in Networked Systems under Denial-of-Service attacks

We consider the joint design of control and scheduling under stochastic Denial-of-Service (DoS) attacks in the context of networked control systems. A sensor takes measurements of the system output and forwards its dynamic state estimates to a remote controller over a packet-dropping link. The controller determines the optimal control law for the process using the estimates it receives. An attacker aims at degrading the control performance by increasing the packet-dropout rate with a DoS attack towards the sensor-controller channel. Assume both the controller and the attacker are rational in a game-theoretic sense. We establish a partially observable stochastic game to derive the optimal joint design of scheduling and control. Using dynamic programming we prove that the control and scheduling policies can be designed separately without sacrificing optimality, making the problem equivalent to a complete information game. We employ Nash Q-learning to solve the problem and prove that the solution is guaranteed to constitute an $\epsilon$-Nash equilibrium. Numerical examples are provided to illustrate the tradeoffs between control performance and communication cost.Comment: 9 pages, 4 figure