Security Of Networked Control Systems Research Articles

Novel Dynamic Defense Strategies in Networked Control Systems under Stochastic Jamming Attacks

In contemporary networked control systems (NCSs), ensuring robust and adaptive security measures against dynamic threats like jamming attacks is crucial. These attacks can disrupt the control signals, leading to degraded performance or even catastrophic failures. This paper introduces a novel approach to enhance NCS security by applying stochastic game theory to model and resolve interactions between a defender and a jammer. We develop a two-player zero-sum game where the defender employs mixed strategies to minimize the expected cost of maintaining system stability and control effectiveness in the face of potential jamming. Our model discretizes the state space and employs backward induction to dynamically update the value functions associated with various system states, reflecting the ongoing adjustment of strategies in response to the adversary’s actions. Utilizing linear programming in MATLAB, we optimize the defender’s mixed strategies to systematically mitigate the impact of jamming. The results from extensive simulations demonstrate the efficacy of our proposed strategies in attack scenarios, indicating a substantial enhancement in the resilience and performance of NCSs against jamming attacks. Specifically, the proposed method improved network state stability by 75%, reducing the fluctuation range by over 50% compared with systems without defense mechanisms. This study not only advances the theoretical framework for security in NCSs but also provides practical insights for the design of resilient control systems under uncertainty.

Secure Control of Linear Controllers Using Fully Homomorphic Encryption

In actual operation, there are security risks to the data of the network control system, mainly in the form of possible eavesdropping of signals in the transmission channel and parameters in the controller leading to data leakage. In this paper, we propose a scheme for encrypting linear controllers using fully homomorphic encryption, which effectively removes these security risks and substantially improves the security of networked control systems. Meanwhile, this paper uses precomputation to handle data encryption, which eliminates the encryption time and solves the drawback of fully homomorphic encryption that it is difficult to apply due to the efficiency problem. Compared to previous schemes with precomputation, for the first time, we propose two methods to mitigate the problem of the slight security degradation caused by precomputation, which makes our scheme more secure. Finally, we provide numerical simulation results to support our scheme, and the data show that the encrypted controller achieves normal control and improves safety and efficiency.

Privacy and Security in Network Controlled Systems via Dynamic Masking

In this paper, we propose a new architecture to enhance the privacy and security of networked control systems against malicious adversaries. We consider an adversary which first learns the system using system identification techniques (privacy), and then performs a data injection attack (security). In particular, we consider an adversary conducting zero-dynamics attacks (ZDA) which maximizes the performance cost of the system whilst staying undetected. Using the proposed architecture, we show that it is possible to (i) introduce significant bias in the system estimates obtained by the adversary: thus providing privacy, and (ii) efficiently detect attacks when the adversary performs a ZDA using the identified system: thus providing security. Through numerical simulations, we illustrate the efficacy of the proposed architecture.

On the Security of Networked Control Systems in Smart Vehicle and Its Adaptive Cruise Control

With the benefits of Internet of Vehicles (IoV) paradigm, come along unprecedented security challenges. Among many applications of inter-connected systems, vehicular networks and smart cars are examples that are already rolled out. Smart vehicles not only have networks connecting their internal components e.g. via Controller Area Network (CAN) bus, but also are connected to the outside world through road side units and other vehicles. In some cases, the internal and external network packets pass through the same hardware and are merely isolated by software defined rules. Any misconfiguration opens a window for the hackers to intrude into vehicles’ internal components e.g. central lock system, Engine Control Unit (ECU), Anti-lock Braking System (ABS) or Adaptive Cruise Control (ACC) system. Compromise of any of these can lead to disastrous outcomes. In this paper, we study the security of smart vehicles’ adaptive cruise control systems in the presence of covert attacks. We define two covert/stealth attacks in the context of cruise control and propose a novel intrusion detection and compensation method to disclose and respond to such attacks. More precisely, we focus on the covert cyber attacks that compromise the integrity of cruise controller and employ a neural network identifier in the IDS engine to estimate the system output dynamically and compare it against the ACC output. If any anomaly is detected, an embedded substitute controller kicks in and takes over the control. We conducted extensive experiments in MATLAB to evaluate the effectiveness of the proposed scheme in a simulated environment.

Event-triggered Approach to Increasing Sampling Period of Encrypted Control Systems

Controller encryption is a cryptographic approach to enhancing the security of networked control systems. The method would be effective in reducing risks of eavesdropping attacks. However, encryption may cause high communication traffic and processing delays. This study proposes a redetermination method for a sampling period of a given encrypted control system to increase the sampling period. The proposed method can reduce the bit rate of communication between a plant and controller and improving the strength of ciphertexts. The validity of the proposed method is examined through numerical simulations. The simulation results demonstrate that the sampling period-redetermined encrypted control system achieves asymptotic stability and retains control performance of the original encrypted control system.

A novel set-membership estimation approach for preserving security in networked control systems under deception attacks

This paper is concerned with the security problem for a networked control system subject to deception attacks. An adversary is present to corrupt both the sensor-to-controller channel and the controller-to-actuator channel with deception signals when sensor and control data are transmitted via the network medium. We model the malicious deception signals as unknown-but-bounded signals in such a way that no priori knowledge of the attack signals is required. First, a delicate set-membership performance index is proposed for meeting the system security requirement. Second, a novel set-membership estimation method is developed to obtain the desired ellipsoidal estimation set which guarantees the enclosing of true state of the system at every instant of time. Such an ellipsoidal estimation set is then used for deriving the sufficient conditions such that the resulting closed-loop system is set-membership input-to-state-stable and achieves the prescribed security requirement. Finally, a target tracking system is given to demonstrate the effectiveness of the proposed method.

Adaptive dynamic programming for security of networked control systems with actuator saturation

In this paper, an optimal control problem is investigated for a networked control system with actuator saturation under denial-of-service attacks. An intrusion detection system is introduced to defend denial-of-service attacks in the networked control system. Game theory is used to describe interaction between denial-of-service attacks and the intrusion detection system. A performance index function is presented to deal with actuator saturation by an iterative adaptive dynamic programming algorithm. Back-propagation neural networks are used to realize the iterative adaptive dynamic programming algorithm. Two numerical simulations are given to demonstrate effectiveness of the proposed method.

A brief overview on secure control of networked systems

This paper focuses on the issues of the security of networked control systems by summarizing recent progress in secure control of this research and application area. We mainly discuss existing results, especially in modeling issues, of three aspects: (1) attack mechanisms and their impacts on control systems, (2) the identification and design of attacks, and (3) secure estimation and control strategies. A conclusion is drawn at the end of this paper. In addition, several promising research tendencies of the development for secure control in networked control system are presented.

Minimum Resource Commitment for Reachability Specifications in a Discrete Time Linear Setting

This paper addresses control input design for a discrete time linear system. The goal is to satisfy a reachability specification and, at the same time, minimize the number of inputs that need to be set (influential inputs). To this purpose, we introduce an appropriate input parametrization so that, depending on the parameter values, some of the inputs act as control variables, while the others are treated as disturbances and can take an arbitrary value in their range. We then enforce the specification while maximizing the number of disturbance inputs. Two approaches are developed: one based on an open-loop scheme and one based on a compensation scheme. In the former, we end up solving a linear program. In the latter, the parametrization is extended so as to allow the influential inputs to depend on the non-influential ones, and the problem is reduced to a mixed integer linear program. A comparison between the two approaches is carried out, showing the superiority of the latter. Possible applications to system design and security of networked control systems are briefly discussed in the introduction.

Cyberphysical Security in Networked Control Systems [About This Issue

Summarizes the articles included in this issue of the publication.

Cyberphysical Security in Networked Control Systems: An Introduction to the Issue

This special issue provides an introduction to cyberphysical security of networked control systems (NCSs) and summarizes recent progress in applying fundamentals of systems theory and decision sciences to this new and increasingly promising area. NCS applications range from large-scale industrial applications to critical infrastructures such as water, transportation, and electricity networks. The security of NCSs naturally depends on the integration of cyber and physical dynamics and on different ways in which they are affected by the actions of human decision makers. Thus, problems in this area lie at the intersection of control systems and computer security. The six articles that constitute this special issue approach cyberphysical security from a variety of perspectives, including control theory, optimization, and game theory. They cover a range of topics such as models of attack and defense, risk assessment, his special issue provides an introduction to cyberphysical security of networked control systems (NCSs) and summarizes recent progress in applying fundamentals of systems theory and decision sciences to this new and increasingly promising area. NCS applications range from large-scale industrial applications to critical infrastructures such as water, transportation, and electricity networks. The security of NCSs naturally depends on the integration of cyber and physical dynamics and on different ways in which they are affected by the actions of human decision makers. Thus, problems in this area lie at the intersection of control systems and computer security. The six articles that constitute this special issue approach cyberphysical security from a variety of perspectives, including control theory, optimization, and game theory. They cover a range of topics such as models of attack and defense, risk assessment,attack detection and identification, and secure control design.A common theme among these contributions is an emphasis on the development of a principled approach to cyberphysical security of NCS.

Monitoring Security of Networked Control Systems: It's the Physics

Physical device safety is typically implemented locally using embedded controllers, whereas operations safety is primarily performed in control centers. Safe operations can be enhanced by correctly designed device-level control algorithms as well as protocols, procedures, and operator training at the control-room level, but all of these can fail. Moreover, these elements exchange data and issue commands via vulnerable communication layers. To secure these gaps and enhance operational safety, the authors believe command sequence monitoring must be combined with an awareness of physical device limitations and automata models that capture safety mechanisms. One way of doing this is by leveraging specification-based intrusion detection to monitor for physical constraint violations. This method can also verify that the physical infrastructure state is consistent with information and commands exchanged by controllers. This additional security layer enhances protection from both outsider attacks and insider mistakes.

Optimal Tradeoff Between Performance and Security in Networked Control Systems Based on Coevolutionary Algorithms

Networked control systems (NCS) have to be well protected with security mechanisms from malicious attackers on the network (e.g., Internet). However, the additional security mechanism might sacrifice the performance of the NCS due to limited system resources. This paper addresses the issue of the tradeoff between NCS security and the NCS real-time performance. Using a networked DC motor system as an example, a tradeoff model for performance and security on NCS is presented. This paper also presents a framework of performance-security tradeoff optimization based on coevolutionary genetic algorithm (CGA) for the networked DC motor system. Experiments show that CGA is highly efficient in finding the Nash equilibrium for the tradeoff model on NCS. The framework presented in this paper is also demonstrated to be an effective approach for performance-security tradeoff analysis and optimization on NCS.