An Overview on Denial-of-Service Attacks in Control Systems: Attack Models and Security Analyses

Maintaining Cyber Resilience in the Reconfigurable Networks with Immunization and Improved Network Game Methods

The paper proposes a technique for protecting reconfigurable networks that implements topology rebuilding, which combines immunization and network gaming methods, as a solution for maintaining cyber resilience. Immunization presumes an adaptive set of protective reconfigurations destined to ensure the functioning of a network. It is a protective reconfiguration aimed to preserve/increase the functional quality of the system. Network nodes and edges are adaptively reorganized to counteract an invasion. This is a functional component of cyber resilience. It can be implemented as a global strategy, using knowledge of the whole network structure, or a local strategy that only works with a certain part of a network. A formal description of global and local immune strategies based on hierarchical and peer-to-peer network topologies is presented. A network game is a kind of the well-defined game model in which each situation generates a specific network, and the payoff function is calculated based on the constructed networks. A network game is proposed for analyzing a network topology. This model allows quickly identifying nodes that require disconnection or replacement when a cyber attack occurs, and understanding which network sectors might be affected by an attack. The gaming method keeps the network topology resistant to unnecessary connections. This is a structural component of cyber resilience. The basic network game method has been improved by using the criterion of maximum possible path length to reduce the number of reconfigurations. Network optimization works together with immunization to preserve the structural integrity of the network. In an experimental study, the proposed method demonstrated its effectiveness in maintaining system quality within given functional limits and reducing the cost of system protective restructuring.

Almost Sure Stability of Complex-Valued Complex Networks: A Noise-Based Delayed Coupling Under Random Denial-of-Service Attacks

This article is concerned with stability for stochastic complex-valued delayed complex networks under random denial-of-service (RDoS) attacks. Different from the existing literature on the stability of stochastic complex-valued systems that concentrate on moment stability, we investigate almost sure stability (ASS), where noise plays a stabilizing role. It is noted that, besides the vertex systems influenced by noise, the interactions among vertices are also at the mercy of noise. As a consequence, an innovative noise-based delayed coupling (NDC) in the presence of RDoS attacks is proposed first to accomplish the stability of complex-valued networks, where the RDoS attacks have a certain probability of triumphantly interfering with communications at active intervals of attackers. Namely, RDoS attacks considered are randomly launched at active periods, which is more realistic. In terms of the Lyapunov method and stochastic analysis theory, an almost sure exponential stability (ASES) criterion of the system discussed straightforwardly is developed by constructing a delay-free auxiliary system, while removing the traditional assumption of moment stability. The criterion strongly linked with topological structure, RDoS frequency, attack successful probability, and noise intensity reveals that the higher the noise intensity, the faster the convergence rate is for the stability of the network. In light of the criterion established, we present an algorithm that can be employed to analyze the tolerable attack parameters and the upper bound of the coupling delays, under the prerequisite of guaranteeing the stability of the network. Eventually, the theoretical results are applied to inertial complex-valued neural networks (ICNNs) and an illustrative example is presented to substantiate the efficiency of the theoretical works.

Trajectory tracking control for a quadrotor helicopter in the presence of cyber attacks

In this paper, the secure trajectory tracking issue is investigated for a quadrotor helicopter system with unknown-but-bounded (UBB) noises. It is assumed that the generated reference trajectory is sent to the helicopter via wireless networks which could be vulnerable to malicious attacks. The proposed encoding-decoding approach (EDA) can significantly improve the attack detection rate (DR), which is designed as a monotone and continuous function. Moreover, it is illustrated that both the DR and the tracking error can be affected by the parameter of the EDA. In addition, the zonotopic unknown input observer (ZUIO) is designed to estimate the helicopter's states, which can be utilized to deal with UBB noises. Then, the gains of both the controller and the ZUIO can be calculated by minimizing the P-radius of the corresponding zonotopes. Finally, numerical examples are provided to demonstrate that the parameter of EDA can increase the DR and decrease the false alarm rate (FAR).

A Brief Survey of Recent Advances and Methodologies for the Security Control of Complex Cyber-Physical Networks

Complex cyber-physical networks combine the prominent features of complex networks and cyber-physical systems (CPSs), and the interconnections between the cyber layer and physical layer usually pose significant impacts on its normal operation. Many vital infrastructures, such as electrical power grids, can be effectively modeled as complex cyber-physical networks. Given the growing importance of complex cyber-physical networks, the issue of their cybersecurity has become a significant concern in both industry and academic fields. This survey is focused on some recent developments and methodologies for secure control of complex cyber-physical networks. Besides the single type of cyberattack, hybrid cyberattacks are also surveyed. The examination encompasses both cyber-only hybrid attacks and coordinated cyber-physical attacks that leverage the strengths of both physical and cyber attacks. Then, special focus will be paid to proactive secure control. Reviewing existing defense strategies from topology and control perspectives aims to proactively enhance security. The topological design allows the defender to resist potential attacks in advance, while the reconstruction process can aid in reasonable and practical recovery from unavoidable attacks. In addition, the defense can adopt active switching-based control and moving target defense strategies to reduce stealthiness, increase the cost of attacks, and limit the attack impacts. Finally, conclusions are drawn and some potential research topics are suggested.

Secure Event-Triggered Consensus Control of Linear Multiagent Systems Subject to Sequential Scaling Attacks

This article investigates secure consensus of linear multiagent systems under event-triggered control subject to a scaling deception attack. Different from probabilistic models, a sequential scaling attack is considered, in which specific attack properties, such as the attack duration and frequency, are defined. Moreover, to alleviate the utilization of communication resources, distributed static and dynamic event-triggered control protocols are proposed and analyzed, respectively. This article aims at providing a resilient event-triggered framework to defend a kind of sequential scaling attack by exploring the relationship among the attack duration and frequency, and event-triggered parameters. First, the static event-triggered control is studied, and sufficient consensus conditions are derived, which impose constraints on the attack duration and frequency. Second, a state-based auxiliary variable is introduced in the dynamic event-triggered scheme. Under the proposed dynamic event-triggered control, consensus criteria involving triggering parameters, attack constraints, and system matrices are obtained. It proves that the Zeno behavior can be excluded. Moreover, the impacts of the scaling factor, triggering parameters, and attack properties are discussed. Finally, the effectiveness of the proposed event-triggered control mechanisms is validated by two examples.

Event-triggering control scheme for discrete time Cyberphysical Systems in the presence of simultaneous hybrid stochastic attacks

Industry Revolution 4.0 pushes the industry to digitize all its operations. Cyberphysical Systems (CPSs), such as autonomous automobile systems and medical monitoring are examples of this revolution. However, as these systems are interconnected via the Internet, they become more vulnerable to cyber-attacks and in particular, stealthy attacks. Cyber attacks could affect the operations of CPS and cause physical damages before any indication. So, there is a need to design a secure control system to withstand in these circumstances. In this article, an event-triggering control scheme is designed for discrete time CPSs contain random delays in measurements and actuation signals and subject to simultaneous hybrid distributed denial of service (DDoS) and deception attacks. The cyber attacks are designed as Bernoulli distributed white sequences with conditional probabilities that are variable. Moreover, An event-triggering control scheme is proposed for decreasing the communication overhead in the system, such that the measurements' signals are sent when a selected triggering condition is met. An observer based control is designed to maintain the stability of the CPS under all possible scenarios of single or hybrid simultaneous attacks in the forward and or backward communication. Linear matrix inequalities are used to represent the overall control scheme. At the end, two illustrative examples are presented and discussed to show the effectiveness of the presented scheme.

On Consensus and Stability under Denial-of-Service Attacks

In the paper, discrete-time multi-agent systems under Denial-of-Service (DoS) attacks are considered. Since in the presence of DoS attacks the stability of the whole system may be disturbed, sufficient stability conditions for the multi-agent system under DoS attacks are delivered. The consensus problem for the special case of the considered system under DoS attacks is also examined by delivering sufficient conditions. Theoretical considerations are illustrated by numerical examples.

Stochastic model predictive control framework for resilient cyber-physical systems: review and perspectives

In the era of Industrial 4.0, the next-generation control system regards the cyber-physical system (CPS) as the core ingredient thanks to the comprehensive integration of physical systems, online computation, networking and control. A reliable, stable and resilient CPS should pledge robustness and safety. A significant concern in CPS development arises from security issues since the CPS is vulnerable to physical constraints, ubiquitous uncertainties and malicious cyber attacks. The integration of the stochastic model predictive control (MPC) framework and the resilient mechanism is a possible approach to guarantee robustness in the presence of stochastic uncertainties and enable resilience against cyber attacks. This review paper aims to offer a detailed overview of existing stochastic MPC algorithms and their CPS applications. More specifically, we first review existing stochastic MPC algorithms for both linear and nonlinear systems subject to probabilistic constraints. We then discuss how to extend the stochastic MPC framework to incorporate resilience mechanisms for constrained CPS under various malicious attacks. Finally, we present an architectural stochastic MPC-based framework for resilient CPS and identify future research challenges. This article is part of the theme issue 'Towards symbiotic autonomous systems'.

Resilient Green Cellular IoT for Landslide Monitoring Using Voice Channels

A wide-scale outdoor remote deployment involves a large number of low-cost nodes that are powered by green energy, such as solar. We deal with such a system for landslide monitoring where the tiny nodes with ultra-low memory as little as 2 KB are directly connected to the Internet using cellular networks, thereby constituting Cellular IoT’s (C-IoT). This makes them vulnerable to a wide range of Denial of Service (DoS) attacks during their collaborative communications. Further, due to memory constraints, the nodes are not able to run resource-hungry security algorithms. Existing IoT protocols also cannot offer resiliency to DoS attacks for these memory-constrained devices. This paper proposes the Voice Response Internet of Things (VRITHI), which addresses the above issues by using the voice channel between the nodes. To the best of our knowledge, this is the first solution in the IoT domain where both the voice and data channels are being used for collaborative communications. Evaluation results demonstrate that VRITHI is able to reduce external DoS attacks from 82–65% to less than 28% and improves real-time communications in such a memory-constrained environment. In addition, it also contributes to green IoT energy saving by more than 50% in comparison with other IoT protocols.

A Survey on Machine-Learning Based Security Design for Cyber-Physical Systems

A cyber-physical system (CPS) is the integration of a physical system into the real world and control applications in a computing system, interacting through a communications network. Network technology connecting physical systems and computing systems enables the simultaneous control of many physical systems and provides intelligent applications for them. However, enhancing connectivity leads to extended attack vectors in which attackers can trespass on the network and launch cyber-physical attacks, remotely disrupting the CPS. Therefore, extensive studies into cyber-physical security are being conducted in various domains, such as physical, network, and computing systems. Moreover, large-scale and complex CPSs make it difficult to analyze and detect cyber-physical attacks, and thus, machine learning (ML) techniques have recently been adopted for cyber-physical security. In this survey, we provide an extensive review of the threats and ML-based security designs for CPSs. First, we present a CPS structure that classifies the functions of the CPS into three layers: the physical system, the network, and software applications. Then, we discuss the taxonomy of cyber-physical attacks on each layer, and in particular, we analyze attacks based on the dynamics of the physical system. We review existing studies on detecting cyber-physical attacks with various ML techniques from the perspectives of the physical system, the network, and the computing system. Furthermore, we discuss future research directions for ML-based cyber-physical security research in the context of real-time constraints, resiliency, and dataset generation to learn about the possible attacks.

CNA Tactics and Techniques: A Structure Proposal

Destructive and control operations are today a major threat for cyber physical systems. These operations, known as Computer Network Attack (CNA), and usually linked to state-sponsored actors, are much less analyzed than Computer Network Exploitation activities (CNE), those related to intelligence gathering. While in CNE operations the main tactics and techniques are defined and well structured, in CNA there is a lack of such consensuated approaches. This situation hinders the modeling of threat actors, which prevents an accurate definition of control to identify and to neutralize malicious activities. In this paper, we propose the first global approach for CNA operations that can be used to map real-world activities. The proposal significantly reduces the amount of effort need to identify, analyze, and neutralize advanced threat actors targeting cyber physical systems. It follows a logical structure that can be easy to expand and adapt.

A Comprehensive Review of the Cyber-Attacks and Cyber-Security on Load Frequency Control of Power Systems

Power systems are complex systems that have great importance to socio-economic development due to the fact that the entire world relies on the electric network power supply for day-to-day life. Therefore, for the stable operation of power systems, several protection and control techniques are necessary. The power system controllers should have the ability to maintain power system stability. Three important quantities that should be effectively controlled to maintain the stability of power systems are frequency, rotor angle, and voltage. The voltage control in power systems maintains the voltage and reactive power within the required limits and the power factor control enhances the efficiency of power distribution systems by improving load power factors. Among various controls, the frequency control is the most time-consuming control mechanism of power systems due to the involvement of mechanical parts. As the control algorithms of frequency stabilization deliver control signals in the timescale of seconds, load frequency control (LFC) systems cannot handle complicated data validation algorithms, making them more vulnerable to disturbances and cyber-attacks. In addition, the LFC system has extended digital layers with open communication networks and is designed to operate with less human intervention. Moreover, the frequency fluctuation due to load change or cyber-attack in one area affects all other interconnected areas, and thus threatens the stability of the entire network. Due to these circumstances, research activities are still carried out in the field of frequency control and cyber-security. In this paper, a comprehensive review of the cyber-security of the LFC mechanism in the power system is presented. The highlights of the paper include the identification of attack points of different configurations of the LFC system, discussion of the attack strategies, formulation of various attack models, and a brief review of the existing detection and defense mechanisms against cyber-attacks on LFC.

Editorial: Entropy in Networked Control

This is an editorial article summarizing the scope and contents of the Special Issue Entropy in Networked Control.