An official website of the United States government
Communication networks in power systems are a major part of the smart grid paradigm. It enables and facilitates the automation of power grid operation as well as self-healing in contingencies. Such dependencies on communication networks, though, create a roam for cyber-threats. An adversary can launch an attack on the communication network, which in turn reflects on power grid operation. Attacks could be in the form of false data injection into system measurements, flooding the communication channels with unnecessary data, or intercepting messages. Using machine learning-based processing on data gathered from communication networks and the power grid is a promising solution for detecting cyber threats. In this paper, a co-simulation of cyber-security for cross-layer strategy is presented. The advantage of such a framework is the augmentation of valuable data that enhances the detection as well as identification of anomalies in the operation of the power grid. The framework is implemented on the IEEE 118-bus system. The system is constructed in Mininet to simulate a communication network and obtain data for analysis. A distributed three controller software-defined networking (SDN) framework is proposed that utilizes the Open Network Operating System (ONOS) cluster. According to the findings of our suggested architecture, it outperforms a single SDN controller framework by a factor of more than ten times the throughput. This provides for a higher flow of data throughout the network while decreasing congestion caused by a single controller’s processing restrictions. Furthermore, our CECD-AS approach outperforms state-of-the-art physics and machine learning-based techniques in terms of attack classification. The performance of the framework is investigated under various types of communication attacks.
more »
« less
A Framework for Joint Attack Detection and Control Under False Data Injection
In this work, we consider an LTI system with a Kalman filter, detector, and Linear Quadratic Gaussian (LQG) controller under false data injection attack. The interaction between the controller and adversary is captured by a Stackelberg game, in which the controller is the leader and the adversary is the follower. We propose a framework under which the system chooses time-varying detection thresholds to reduce the effectiveness of the attack and enhance the control performance. We model the impact of the detector as a switching signal, resulting in a switched linear system. A closed form solution for the optimal attack is first computed using the proposed framework, as the best response to any detection threshold. We then present a convex program to compute the optimal detection threshold. Our approach is evaluated using a numerical case study.
more »
« less
- Award ID(s):
- 1656981
- PAR ID:
- 10131727
- Date Published:
- Journal Name:
- IEEE Conference on Decision and Game Theory for Security
- Page Range / eLocation ID:
- 352-363
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
This work focuses on the problem of enhancing cyberattack detection capabilities in process control systems subject to multiplicative cyberattacks. First, the relationship between closed-loop stability and attack detectability with respect to a class of residual-based detection schemes is rigorously analyzed. The results are used to identify a set of controller parameters (called "attack-sensitive" controller parameters) under which an attack can destabilize the closed-loop system. The selection of attack-sensitive controller parameters can enhance the ability to detect attacks, but can also degrade the performance of the attack-free closed-loop system. To balance this trade-off, a novel active attack detection methodology employing controller parameter switching between the nominal controller parameters (chosen on the basis of standard control design criteria) and the attack-sensitive controller parameters, is developed. The proposed methodology is applied to a chemical process example to demonstrate its ability to detect multiplicative sensor-controller communication link attacks.more » « less
-
Cyber-physical systems are conducting increasingly complex tasks, which are often modeled using formal languages such as temporal logic. The system’s ability to perform the required tasks can be curtailed by malicious adversaries that mount intelligent attacks. At present, however, synthesis in the presence of such attacks has received limited research attention. In particular, the problem of synthesizing a controller when the required specifications cannot be satisfied completely due to adversarial attacks has not been studied. In this paper, we focus on the minimum violation control synthesis problem under linear temporal logic constraints of a stochastic finite state discrete-time system with the presence of an adversary. A minimum violation control strategy is one that satisfies the most important tasks defined by the user while violating the less important ones. We model the interaction between the controller and adversary using a concurrent Stackelberg game and present a nonlinear programming problem to formulate and solve for the optimal control policy. To reduce the computation effort, we develop a heuristic algorithm that solves the problem efficiently and demonstrate our proposed approach using a numerical case study.more » « less
-
Software-Defined Networking (SDN) is a dynamic, and manageable network architecture which is more cost-effective than existing network architectures. The idea behind this architecture is to centralize intelligence from the network hardware and funnel this intelligence to the management system (controller) [2]-[4]. Since the centralized SDN controller controls the entire network and manages policies and the flow of the traffic throughout the network, it can be considered as the single point of failure [1]. It is important to find some ways to identify different types of attacks on the SDN controller [8]. Distributed Denial of Service (DDoS) attack is one of the most dangerous attacks on SDN controller. In this work, we implement DDoS attack on the Ryu controller in a tree network topology using Mininet emulator. Also, we use a machine learning method, Vector Machines (SVM) to detect DDoS attack. We propose to install flows in switches, and we consider time attack pattern of the DDoS attack for detection. Simulation results show the effects of DDoS attacks on the Ryu controller is reduced by 36% using our detection method.more » « less
-
Cyber-physical systems (CPS) are susceptible to physical attacks, and researchers are exploring ways to detect them. One method involves monitoring the system for a set duration, known as the time-window, and identifying residual errors that exceed a predetermined threshold. However, this approach means that any sensor attack alert can only be triggered after the time-window has elapsed. The length of the time-window affects the detection delay and the likelihood of false alarms, with a shorter time-window leading to quicker detection but a higher false positive rate, and a longer time-window resulting in slower detection but a lower false positive rate. While researchers aim to choose a fixed time-window that balances a low false positive rate and short detection delay, this goal is difficult to attain due to a trade-off between the two. An alternative solution proposed in this paper is to have a variable time-window that can adapt based on the current state of the CPS. For instance, if the CPS is heading towards an unsafe state, it is more crucial to reduce the detection delay (by decreasing the time-window) rather than reducing the false alarm rate, and vice versa. The paper presents a sensor attack detection framework that dynamically adjusts the time-window, enabling attack alerts to be triggered before the system enters dangerous regions, ensuring timely detection. This framework consists of three components: attack detector, state predictor, and window adaptor. We have evaluated our work using real-world data, and the results demonstrate that our solution improves the usability and timeliness of time-window-based attack detectors.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/https://doi.org/10.1007/978-3-030-32430-8_21
