Modeling Of Cyber-physical Systems Research Articles

Mutation mayfly algorithm (MMA) based feature selection and probabilistic anomaly detection model for cyber-physical systems

Mutation mayfly algorithm (MMA) based feature selection and probabilistic anomaly detection model for cyber-physical systems

An intelligent dynamic cyber physical system threat detection system for ensuring secured communication in 6G autonomous vehicle networks

Smart cities have developed advanced technology that improves people’s lives. A collaboration of smart cities with autonomous vehicles shows the development towards a more advanced future. Cyber-physical system (CPS) are used blend the cyber and physical world, combined with electronic and mechanical systems, Autonomous vehicles (AVs) provide an ideal model of CPS. The integration of 6G technology with Autonomous Vehicles (AVs) marks a significant advancement in Intelligent Transportation Systems (ITS), offering enhanced self-sufficiency, intelligence, and effectiveness. Autonomous vehicles rely on a complex network of sensors, cameras, and software to operate. A cyber-attack could interfere with these systems, leading to accidents, injuries, or fatalities. Autonomous vehicles are often connected to broader transportation networks and infrastructure. A successful cyber-attack could disrupt not only individual vehicles but also public transportation systems, causing widespread chaos and economic damage. Autonomous vehicles communicate with other vehicles (V2V) and infrastructure (V2I) for safe and efficient operation. If these communication channels are compromised, it could lead to collisions, traffic jams, or other dangerous situations. So we present a novel approach to mitigating these security risks by leveraging pre-trained Convolutional Neural Network (CNN) models for dynamic cyber-attack detection within the cyber-physical systems (CPS) framework of AVs. The proposed Intelligent Intrusion Detection System (IIDS) employs a combination of advanced learning techniques, including Data Fusion, One-Class Support Vector Machine, Random Forest, and k-Nearest Neighbor, to improve detection accuracy. The study demonstrates that the EfficientNet model achieves superior performance with an accuracy of up to 99.97%, highlighting its potential to significantly enhance the security of AV networks. This research contributes to the development of intelligent cyber-security models that align with 6G standards, ultimately supporting the safe and efficient integration of AVs into smart cities.

Smart Healthcare Based Cyber Physical System Modeling by Block Chain with Cloud 6G Network and Machine Learning Techniques

Smart Healthcare Based Cyber Physical System Modeling by Block Chain with Cloud 6G Network and Machine Learning Techniques

Event‐triggered secure control under denial‐of‐service attacks for cyber‐physical systems with positive constraint

AbstractThis paper investigates the stabilization problem for cyber‐physical systems subject to positive constraint and denial‐of‐service (DoS) attacks using the event‐triggered scheme. Unlike traditional modeling of cyber physical systems with DoS attack, this paper establishes a positive switched system model composed of two positive subsystems that according to the DoS attack is active or inactive. Considering the effect of positive constraint and DoS attack, a 1‐norm‐based event‐triggered mechanism is proposed in the sleep interval of DoS attacks. By incorporating switching theory with event‐triggered mechanism, the sufficient condition of positive property and exponential stabilization for the considered system is established. Thereafter, the gain matrix of the controller is calculated by matrix decomposition technique. Furthermore, the Zeno behavior is eliminated with a lower bound of the event‐triggered interval. Finally, an example is carried out to verify the validity of the theoretical results.

Data-driven replay attack detection for unknown cyber-physical systems

This paper considers a data-driven method to detect stealthy replay attacks on cyber-physical systems (CPSs) whose models are unknown. Most existing attack detection methods assume the system dynamic is known. However, due to the large scale and complexity of the system, it is difficult to get an accurate model of a CPS. This paper uses a moving window subspace identification method to construct a linear discrete time-varying model of CPS. The controllability and observability of the obtained model are proved. On this basis, the replay attack is transformed into a detectable additive attack using the output coding strategy. Then, considering modeling errors, a time-varying H∞ filter is designed, and a detection function based on the output residual is constructed. When the system works without any attacks, the detection function approaches a limited threshold. On the contrary, that function will increase extremely larger than the threshold when the replay attack occurs. The detectability of our scheme for attacks is also mathematically proven. Finally, to verify the effectiveness of the proposed scheme, we provide simulation results on a linear motor system and a nonlinear robotic system.

A Risk Assessment Framework for Cyber-Physical Security in Distribution Grids with Grid-Edge DERs

Integration of inverter-based distributed energy resources (DERs) is reshaping the landscape of distribution grids to fulfill the socioeconomic, environmental, and sustainability goals. Addressing the technological challenges of DER grid integration requires an adaptive communication layer for efficient DER management and control. This transition has given rise to a cyberphysical system (CPS) architecture within the distribution system, causing new vulnerabilities for cyberphysical attacks. To better address potential threats, this paper presents a comprehensive risk assessment framework for cyberphysical security in distribution grids with grid-edge DERs. The framework incorporates a detailed CPS model accounting for dynamic DER characteristics within the distribution grid. It identifies vulnerabilities in DER communication systems, models attack scenarios, and addresses communication latency crucial for inverter control timescales. Subsequently, the quantification of attack impacts employs an attack probability model including both the vulnerability and criticality of cyber components. The proposed risk assessment framework was validated through testing on the modified IEEE 13-node and 123-node test feeders.

Robustness assessment of weakly coupled cyber-physical power systems under multi-stage attacks

Evaluating the robustness of cyber-physical system (CPS) under multi-stage attacks is fundamental to enhancing CPS resilience. Currently, many models inadequately consider information flow, which is not aligned with reality. The initial focus of this paper is on introducing a weakly coupled interdependent model for CPS. This model considers probabilistic line outage rules, cyber flow transmission characteristics, and the probabilities of inter-system coupling failures. Subsequently, the multi-stage attack strategies are presented and employed by the proposed model during disaster scenarios, along with the proposed robustness assessment indicators. The numerical results illustrate the robustness of the weakly-coupled CPS model under multi-stage attacks. This lays a modeling and simulation foundation for repair crew to enhance the CPS resilience.

Digital twin method and application practice of spacecraft system driven by mechanism data

Spacecrafts are large-scale systems characterized by various on-orbit configurations, multi-disciplinary coupling, and complex mission modes. Research and exploration on the data-driven spacecraft digital twins development methods must be carried out to satisfy various requirements such as spacecraft on-orbit condition monitoring and risk warning, fast flight conditions predictions, intelligent failure location, and virtual verification of failure. In this paper, significant progress is made in multiple key technologies, such as cyber-physical system modeling and simulation, hybrid modeling and model evolution through mechanism-data fusion, and interactive virtual-reality perception and mapping. The spacecraft digital twins’ model is constructed, and the spacecraft digital twin’s platform is designed and developed. Multiple digital twins’ application scenarios, such as on-orbit mission simulation and emulation, real-time interactive monitoring, and fast operating condition prediction, are supported. The research results are applied to the key on-orbit operation tasks, such as entering orbit, rendezvous and docking, position conversion, and astronaut exiting, enabling system-level digital operation for the sub-systems of spacecraft such as energy, power, control, and communication sub-systems.

Security and Safety in Cyber-Physical System (CPS): An Inclusive Threat Model

A Cyber-Physical System (CPS) is a combination of computational algorithms and physical processes that are integrated together. Cyber-Physical Systems (CPS) integrate computer and communication capabilities with the monitoring and management of physical parts, establishing a mutually beneficial interaction between the cyber and physical components. Industrial Control System (ICS) is one example of CPS which integrates the physical (OT) and cyber domains (IT), which makes them more vulnerable to attacks. Two essential characteristics of Cyber-Physical Systems (CPS) are safety and security. Threat models are methods for identifying, analysing, and proposing security control countermeasures for threats and their capabilities. However, the threat model methods which are used for the traditional IT systems are not sufficient as they do not include the physical interactions, consequences and impacts to the safety aspects in the Operational Technology (OT). On the other hand, a risk assessment analyses attack scenario, examines cybersecurity from the attacker's point of view, and gives cost-benefit data to support the expenditure on security measures. This study proposes an inclusive attacker’s centric threat model and pro-active risk assessment model for CPS using Mamdani Fuzzy Inference System (FIS). The outcomes of the threat model prove that the lateral propagation of the threat is possible and threat may also propagate from the CPS assets to the IT segment. The risk assessment by using FIS shown that the safety and security risk for the CPS is significant and calculated as medium level. Hence, the risk factors that are considered in calculating the overall risk for a CPS need to be immediately addressed and mitigated.

Dynamics of cascading failure in cyber-physical power systems from cyber attack

Abstract Through communication network, cyber-physical power systems can effectively monitor and control physical power grid, but this also increases the danger to systems from cyber attack. In this paper, we study the cascading failure triggered by cyber attack, which infects cyber nodes through malware and to endanger physical nodes through coupling links. First, the flow and topology models for cyber-physical power systems are detailed. In communication network, we analyze the mechanism of diffusion and infection among cyber nodes, and differentiate cyber nodes into three types, corresponding to different state of cyber nodes before and after cyber attack. And in physical power grid, the types of physical nodes are also classified. For different state of cyber nodes, we detail their impact on physical nodes and power flows in physical power grid. Simulation analyzes the robustness of systems and dynamics of cascading failure in different attack scenes and topology structure.

Review of methods for modeling and control of cyber-physical systems in multi-energy microgrids

The article analyzes the development of methods for modeling and control of multi-energy microgrids through cyber-physical systems. We used the methods of literature review and meta-analysis based on publications from international databases Scopus and Web of Science, Russian database eLibrary, digital platform IEEEXplore et al. According to the analysis, Smart Grid implementation drives the development of cyber-physical systems. As summarized in this study, control interfaces, data transmission channels, and remote debugging ports are vulnerable parts of IoT devices that can possibly be attacked by intruders. A review of the recent publications in this field finds multi-agent technologies to be an effective approach not only for the operational control of multi-energy microgrid modes, but also for the construction of its reliable information network at the level of medium and low voltage systems. In the field of distributed energy systems, literature review of information technology indicates that the more capabilities are added to receive and process various kinds of information (transaction data, mode parameters, status of controllers, etc.) from external sources, the more vulnerable a multi-energy microgrid is to any cyber threats. Modern mathematical methods such as artificial intelligence, dynamic optimization, and multi-agent approaches should be used to effectively solve the problem of load distribution between different energy sources with cost minimization.

Distributed Adaptive Robust Restoration Scheme of Cyber-Physical Active Distribution System With Voltage Control

The increasing penetration of distributed generators (DGs) and the advancement of information and communication technologies (ICTs) will facilitate the transformation of the traditional passive distribution network towards a cyber-physical active distribution system (CPADS). With the increasing risks of extreme events, such as natural disasters (e.g., flooding) and cyber-physical attacks, it is critical for CPADS to formulate a restoration scheme to improve its resilience. Therefore, in this paper, a distributed adaptive robust restoration scheme with voltage/var control is presented to cope with the high-impact but low-frequency events. First, a detailed cyber-physical system model is established, including the dynamic routing and the quality-of-services (QoS) in both optical fiber networks and 5G wireless networks. Then, the interactions between the cyber system and the physical system are analyzed. Based on the cyber-physical system model, a two-stage restoration scheme with voltage/var control is proposed by coordinately scheduling different network assets in day-ahead and in real-time. The formulated problem is solved by adaptive robust optimization (ARO). To further enhance the resilience of the CPADS, a distributed restoration framework is proposed. The distributed problem is solved by the alternating direction method of multipliers (ADMM) algorithm, and the convergence of the discrete problem is ensured by introducing the alternating optimization procedure (AOP). Considering the cyber faults, a boundary variable compensation and residual relaxation mechanism is proposed in ADMM. The proposed framework and methodology are verified in the case study. The convergence and the efficiency of the proposed algorithm are verified. Compared with the state-of-art works, the advantages in load restoration capability of the proposed method are shown.

Preliminary investigation of the state of the art on digital servitization for Industrial Asset lifecycle Management

This paper aims to investigate how digital servitization can act as a game changer of Industrial Asset lifecycle Management in manufacturing. Building on a literature review, two main research streams are identified when talking about digital servitization for asset management. A part of the analyzed papers reports the Product-Service Systems as the solutions developed by Original Equipment Manufacturers for managing users’ industrial assets; this primarily focuses on the required change of the value proposition in the offerings due to business models. These papers address a few asset-related processes like the real-time status/process monitoring, or the prognosis and diagnosis of failures. A higher collection of the identified papers addresses the opportunities brought by digitalization to the users of the assets for developing digital services; this involves more actors, and leverages both data-sharing and collaboration. A good portion of this research stream considers the digital capabilities from advanced platforms enabled by infrastructures as Cyber-Physical Systems and Digital Twin models for developing smart services solutions. The digital platforms, open and interoperable, appear to be a promising means where to start from in order to develop the collaborative approaches required by Industrial Asset lifecycle Management; correspondingly, a wider set of asset-related processes can be supported.

A Method for Building Trustworthy Hybrid Performance Models for Cyber-Physical Systems of Systems

A Method for Building Trustworthy Hybrid Performance Models for Cyber-Physical Systems of Systems

Multi-agent modelling of cyber-physical systems for IEC 61499-based distributed intelligent automation

ABSTRACT Traditional industrial automation systems developed under centralized architectures are statically programmed with determined procedures to perform predefined tasks in structured environments. The major challenges for these legacy systems are that they are unable to automatically discover alternative solutions, flexibly coordinate reconfigurable modules and actively deploy corresponding functions, to quickly respond to frequent changes and intelligently adapt to evolving requirements in dynamic environments. This paper presents a two-layer architecture modelling framework, including the high-level cyber module designed as multi-agent computing model and the low-level physical module designed as agent-embedded IEC 61499 function block model, to enable real-time adaptation at the device level and run-time intelligence throughout the whole system. The design results in a new computing module for high-level multi-agent-based automation architectures and a new design pattern for low-level function block modelled control solutions. The design is demonstrated and evaluated through various tests on the multi-agent simulation model developed in NetLogo and the experimental testbed designed on the Jetson Nano and Raspberry Pi platforms. The result shows that the design is feasible with improved performances and expected capabilities to respond to major challenges in Industry 4.0.

Nonfragile security control for time‐varying cyber‐physical systems operating over multipath networks

AbstractThe main focus of this article is to explore the finite‐time stabilization of time‐varying cyber‐physical systems (CPS) that are operating over multipath networks and under random denial‐of‐service (DoS) attacks. In contrast to prior studies, we present a set of necessary and sufficient conditions for achieving finite‐time stability in the closed‐loop model of CPS operating over single‐path network. Notably, this equivalent conditions are established based on the analysis of the state transition matrix (STM). Additionally, we utilized auxiliary systems to study more general CPS operating over multipath networks and obtained a sufficient condition based on STM. Finally, we address a sufficient condition based on the Lyapunov function and introduce a linear matrix inequality (LMI)‐based approach that facilitates the computation of nonfragile controllers. The effectiveness of the developed theoretical results is verified through a stock investment model.

On proving that an unsafe controller is not proven safe

Cyber-physical systems are often safety-critical and their correctness is crucial, such as in the case of automated driving. Using formal mathematical methods is one way to guarantee correctness and improve safety. Although these methods have shown their usefulness, care must be taken because modelling errors might result in proving a faulty controller safe, which is potentially catastrophic in practice. This paper deals with two such modelling errors in differential dynamic logic, a formal specification and verification language for hybrid systems, which are mathematical models of cyber-physical systems. The main contributions are to provide conditions under which these two modelling errors cannot cause a faulty controller to be proven safe, and to show how these conditions can be proven with help of the interactive theorem prover KeYmaera X. The problems are illustrated with a real world example of a safety controller for automated driving, and it is shown that the formulated conditions have the intended effect both for a faulty and a correct controller. It is also shown how the formulated conditions aid in finding a loop invariant candidate to prove properties of hybrid systems with feedback loops. Furthermore, the relation between such a loop invariant and the characterisation of the maximal control invariant set is discussed.

Information-driven cooperation on adaptive cyber-physical systems

Cooperation among competitive populations hinges on trustworthy information usually obtained through personal experiences (private information) and social influence (public information) which often is obtained through interactions in the cyberspace. To reveal the coupled dynamics between information propagation on the cyberspace and evolutionary games in the physical world, we propose a double-layer dynamical graph model for adaptive cyber-physical systems. The reputation information aggregated from the cyber layer can be used for the decision-making in the physical layer, meanwhile the population evolution and competition in the physical layer will reorganise the information network in the cyber layer. Our results show that public and private information on the trustworthiness of others can play significantly different roles in the decision-making to cooperate or defect, leading to very different performance in the global prosperity of the population. Limited consideration for the available public information reduces the benefits of the reorganization of the information network in the cyber layer leading to the increasing of mutual defections. On the other way, when public information is prioritized, the reorganization of the cyber layer can facilitate cooperation. However, the optimal decision-making to maximize population prosperity strongly depends on the way the cyber layer is reorganized and on the opportune balance of public and private information. Our results highlight the importance of the interplay between information reliability and restructuring of the cyber layer for the resilience of cooperation and prosperity in cyber-physical systems.

Bounded model checking for interval probabilistic timed graph transformation systems against properties of probabilistic metric temporal graph logic

Cyber-physical systems often encompass complex concurrent behavior with timing constraints and probabilistic failures on demand. The analysis whether such systems with probabilistic timed behavior adhere to a given specification is essential. The formalism of Interval Probabilistic Timed Graph Transformation Systems (IPTGTSs) is often a suitable choice to model cyber-physical systems because (a) its rule-based approach to graph transformation can capture a wide range of system's structure dynamics when the states of the system can be represented by graphs while (b) it employs interval specifications for probabilistic behavior as well as lower and upper bounds on delays of steps to support systems where precise probabilities and delays are not known or may change during the runtime of the system. Probabilistic Metric Temporal Graph Logic (PMTGL) has been introduced as a powerful specification language to express worst-case/best-case probabilistic timed requirements such as actor-based soft deadlines using (a) path properties relying on its Metric Temporal Graph Logic fragment to track individual graph elements and (b) an operator inherited from Probabilistic Timed Computation Tree Logic to express worst-case/best-case probabilistic requirements identifying worst-case/best-case resolutions of non-determinism. Bounded Model Checking (BMC) support for Probabilistic Timed Graph Transformation Systems (PTGTSs) w.r.t. properties specified using PMTGL has been already presented. However, for IPTGTSs no analysis support w.r.t. PMTGL properties has been developed for stating metric temporal properties on identified subgraphs and their structural changes over time.In this paper, we adapt the BMC approach developed for PTGTSs to the case of IPTGTSs extending modeling and analysis support to the usage of probability intervals more appropriately covering cyber-physical systems where probabilistic effects cannot be specified precisely and need to be approximated instead. In our evaluation, we apply an implementation of our BMC approach in AutoGraph to a novel running example demonstrating the effect of using probability intervals instead of precise probability values.

Digital Process Twins as Intelligent Design Technology for Engineering Metaverse/XR Applications

The last years have seen propagating Metaverse and Mixed Reality (Extended Reality, XR) technologies into everyday applications. Due to their immersion and digitalization capability, sustainability issues can be addressed to optimize resource consumption before processes are put to practice or products are materialized. In particular, Digital Process Twin technologies can execute behavior models of socio-technical Cyber-Physical Systems. They allow both designing variants of system behavior and validating implementation architectures for system operation. In this contribution, I leverage these capabilities to capture the behavior-centered intelligence of Metaverse and XR applications. The more accurately user roles and cyber-physical components can be captured by behavior models representing Metaverse/XR applications, the more accurately the environmental, social, and economic impact of design alternatives can be experienced.