Distributed dynamic event-based finite-time dissipative synchronization control for semi-Markov switched fuzzy cyber-physical systems against random packet losses

This paper is concerned with the finite-time dissipative synchronization control problem of semi-Markov switched cyber-physical systems in the presence of packet losses, which is constructed by the Takagi–Sugeno fuzzy model. To save the network communication burden, a distributed dynamic event-triggered mechanism is developed to restrain the information update. Besides, random packet dropouts following the Bernoulli distribution are assumed to occur in sensor to controller channels, where the triggered control input is analyzed via an equivalent method containing a new stochastic variable. By establishing the mode-dependent Lyapunov–Krasovskii functional with augmented terms, the finite-time boundness of the error system limited to strict dissipativity is studied. As a result of the help of an extended reciprocally convex matrix inequality technique, less conservative criteria in terms of linear matrix inequalities are deduced to calculate the desired control gains. Finally, two examples in regard to practical systems are provided to display the effectiveness of the proposed theory.

Stochastic Models to Mitigate Sparse Sensor Attacks in Continuous-Time Non-Linear Cyber-Physical Systems

Cyber-Physical Systems are very vulnerable to sparse sensor attacks.But current protection mechanisms employ linear and deterministic models which cannot detect attacks precisely.Therefore,in this paper,we propose a new non-linear generalized model to describe Cyber-Physical Systems.This model includes unknown multivariable discrete and continuous-time functions and different multiplicative noises to represent the evolution of physical processes and randomeffects in the physical and computationalworlds.Besides,the digitalization stage in hardware devices is represented too.Attackers and most critical sparse sensor attacks are described through a stochastic process.The reconstruction and protectionmechanisms are based on aweighted stochasticmodel.Error probability in data samples is estimated through different indicators commonly employed in non-linear dynamics(such as the Fourier transform,first-return maps,or the probability density function).A decision algorithm calculates the final reconstructed value considering the previous error probability.An experimental validation based on simulation tools and real deployments is also carried out.Both,the new technology performance and scalability are studied.Results prove that the proposed solution protects Cyber-Physical Systems against up to 92%of attacks and perturbations,with a computational delay below 2.5 s.The proposed model shows a linear complexity,as recursive or iterative structures are not employed,just algebraic and probabilistic functions.In conclusion,the new model and reconstructionmechanism can protect successfully Cyber-Physical Systems against sparse sensor attacks,even in dense or pervasive deployments and scenarios.

Aquila Optimization with Machine Learning-Based Anomaly Detection Technique in Cyber-Physical Systems

Cyber-physical system(CPS)is a concept that integrates every computer-driven system interacting closely with its physical environment.Internet-of-things(IoT)is a union of devices and technologies that provide universal interconnection mechanisms between the physical and digital worlds.Since the complexity level of the CPS increases,an adversary attack becomes possible in several ways.Assuring security is a vital aspect of the CPS environment.Due to the massive surge in the data size,the design of anomaly detection techniques becomes a challenging issue,and domain-specific knowledge can be applied to resolve it.This article develops an Aquila Optimizer with Parameter Tuned Machine Learning Based Anomaly Detection(AOPTML-AD)technique in the CPS environment.The presented AOPTML-AD model intends to recognize and detect abnormal behaviour in the CPS environment.The presented AOPTML-AD framework initially pre-processes the network data by converting them into a compatible format.Besides,the improved Aquila optimization algorithm-based feature selection(IAOA-FS)algorithm is designed to choose an optimal feature subset.Along with that,the chimp optimization algorithm(ChOA)with an adaptive neuro-fuzzy inference system(ANFIS)model can be employed to recognise anomalies in the CPS environment.The ChOA is applied for optimal adjusting of the membership function(MF)indulged in the ANFIS method.The performance validation of the AOPTML-AD algorithm is carried out using the benchmark dataset.The extensive comparative study reported the better performance of the AOPTML-AD technique compared to recent models,with an accuracy of 99.37%.

Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

A Comprehensive Overview of Cyber-Physical Systems: From Perspective of Feedback System

Cyber-physical systems(CPS) are characterized by integrating cybernetic and physical processes. The theories and applications of CPS face the enormous challenges. The aim of this paper is to provide a latest understanding of this emerging multi-disciplinary methodology. First, the features of CPS are described, and the research progresses are summarized from different components in CPS, such as system modeling,information acquisition, communication, control and security.Each part is also followed by the future directions. Then some typical applications are given to show the prospects of CPS.

Review on Cyber-physical Systems

Cyber-physical systems(CPS) are complex systems with organic integration and in-depth collaboration of computation, communications and control(3C) technology. Subject to the theory and technology of existing network systems and physical systems, the development of CPS is facing enormous challenges.This paper first introduces the concept and characteristics of CPS and analyzes the present situation of CPS researches. Then the development of CPS is discussed from perspectives of system model, information processing technology and software design.At last it analyzes the main obstacles and key researches in developing CPS.

Cyber-Physical Systems as General Distributed Parameter Systems:Three Types of Fractional Order Models and Emerging Research Opportunities

Cyber-physical systems(CPSs) are man-made complex systems coupled with natural processes that, as a whole,should be described by distributed parameter systems(DPSs) in general forms. This paper presents three such general models for generalized DPSs that can be used to characterize complex CPSs. These three different types of fractional operators based DPS models are: fractional Laplacian operator, fractional power of operator or fractional derivative. This research investigation is motivated by many fractional order models describing natural, physical, and anomalous phenomena, such as sub-diffusion process or super-diffusion process. The relationships among these three different operators are explored and explained. Several potential future research opportunities are then articulated followed by some conclusions and remarks.

Simulation of Cyber-Physical Systems of Systems： Some Research Areas-Computational Understanding, Awareness, and Wisdom

After a brief emphasis about the interconnected world, including Cyber-Physical Systems of Systems, the increasing importance of the decision-making by autonomous, quasi-autonomous, and autonomic systems is emphasised. Promising roles of computational understanding, computational awareness, and computational wisdom for better autonomous decision-making are outlined. The contributions of simulation-based approaches are listed.

Analysis of cascading failures of power cyber-physical systems considering false data injection attacks

This study considers the performance impacts of false data injection attacks on the cascading failures of a power cyber-physical system,and identifies vulnerable nodes.First,considering the monitoring and control functions of a cyber network and power flow characteristics of a power network,a power cyber-physical system model is established.Then,the influences of a false data attack on the decision-making and control processes of the cyber network communication processes are studied,and a cascading failure analysis process is proposed for the cyber-attack environment.In addition,a vulnerability evaluation index is defined from two perspectives,i.e.,the topology integrity and power network operation characteristics.Moreover,the effectiveness of a power flow betweenness assessment for vulnerable nodes in the cyberphysical environment is verified based on comparing the node power flow betweenness and vulnerability assessment index.Finally,an IEEE14-bus power network is selected for constructing a power cyber-physical system.Simulations show that both the uplink communication channel and downlink communication channel suffer from false data attacks,which affect the ability of the cyber network to suppress the propagation of cascading failures,and expand the scale of the cascading failures.The vulnerability evaluation index is calculated for each node,so as to verify the effectiveness of identifying vulnerable nodes based on the power flow betweenness.

Cyber-Physical Production Systems for Data-Driven,Decentralized,and Secure Manufacturing-A Perspective

With the concepts of Industry 4.0 and smart manufacturing gaining popularity,there is a growing notion that conventional manufacturing will witness a transition toward a new paradigm,targeting innovation,automation,better response to customer needs,and intelligent systems.Within this context,this review focuses on the concept of cyber–physical production system(CPPS)and presents a holistic perspective on the role of the CPPS in three key and essential drivers of this transformation:data-driven manufacturing,decentralized manufacturing,and integrated blockchains for data security.The paper aims to connect these three aspects of smart manufacturing and proposes that through the application of data-driven modeling,CPPS will aid in transforming manufacturing to become more intuitive and automated.In turn,automated manufacturing will pave the way for the decentralization of manufacturing.Layering blockchain technologies on top of CPPS will ensure the reliability and security of data sharing and integration across decentralized systems.Each of these claims is supported by relevant case studies recently published in the literature and from the industry;a brief on existing challenges and the way forward is also provided.

Learning-Based Switched Reliable Control of Cyber-Physical Systems With Intermittent Communication Faults

This study deals with reliable control problems in data-driven cyber-physical systems(CPSs) with intermittent communication faults, where the faults may be caused by bad or broken communication devices and/or cyber attackers. To solve them, a watermark-based anomaly detector is proposed, where the faults are divided to be either detectable or undetectable.Secondly, the fault's intermittent characteristic is described by the average dwell-time(ADT)-like concept, and then the reliable control issues, under the undetectable faults to the detector, are converted into stabilization issues of switched systems. Furthermore,based on the identifier-critic-structure learning algorithm, a datadriven switched controller with a prescribed-performance-based switching law is proposed, and by the ADT approach, a tolerated fault set is given. Additionally, it is shown that the presented switching laws can improve the system performance degradation in asynchronous intervals, where the degradation is caused by the fault-maker-triggered switching rule, which is unknown for CPS operators. Finally, an illustrative example validates the proposed method.

Passivity-Based Robust Control Against Quantified False Data Injection Attacks in Cyber-Physical Systems

Secure control against cyber attacks becomes increasingly significant in cyber-physical systems(CPSs).False data injection attacks are a class of cyber attacks that aim to compromise CPS functions by injecting false data such as sensor measurements and control signals.For quantified false data injection attacks,this paper establishes an effective defense framework from the energy conversion perspective.Then,we design an energy controller to dynamically adjust the system energy changes caused by unknown attacks.The designed energy controller stabilizes the attacked CPSs and ensures the dynamic performance of the system by adjusting the amount of damping injection.Moreover,with the disturbance attenuation technique,the burden of control system design is simplified because there is no need to design an attack observer.In addition,this secure control method is simple to implement because it avoids complicated mathematical operations.The effectiveness of our control method is demonstrated through an industrial CPS that controls a permanent magnet synchronous motor.

A Security Enhancement Model Based on Switching Edge Strategy in Interdependent Heterogeneous Cyber-Physical Systems

With the advent of cross-domain interconnection,large-scale sensor network systems such as smart grids,smart homes,and intelligent transportation have emerged.These complex network systems often have a CPS(Cyber-Physical System)architecture and are usually composed of multiple interdependent systems.Minimal faults between interdependent networks may cause serious cascading failures between the entire system.Therefore,in this paper,we will explore the robustness detection schemes for interdependent networks.Firstly,by calculating the largest giant connected component in the entire system,the security of interdependent network systems under different attack models is analyzed.Secondly,a comparative analysis of the cascade failure mechanism between interdependent networks under the edge enhancement strategy is carried out.Finally,the simulation results verify the impact of system reliability under different handover edge strategies and show how to choose a better handover strategy to enhance its robustness.The further research work in this paper can also help design how to reduce the interdependence between systems,thereby further optimizing the interdependent network system’s structure to provide practical support for reducing the cascading failures.In the later work,we hope to explore our proposed strategies in the network model of real-world or close to real networks.

Decentralized Resilient H_∞Load Frequency Control for Cyber-Physical Power Systems Under DoS Attacks

This paper designs a decentralized resilient H_(∞)load frequency control(LFC)scheme for multi-area cyber-physical power systems(CPPSs).Under the network-based control framework,the sampled measurements are transmitted through the communication networks,which may be attacked by energylimited denial-of-service(DoS)attacks with a characterization of the maximum count of continuous data losses(resilience index).Each area is controlled in a decentralized mode,and the impacts on one area from other areas via their interconnections are regarded as the additional load disturbance of this area.Then,the closed-loop LFC system of each area under DoS attacks is modeled as an aperiodic sampled-data control system with external disturbances.Under this modeling,a decentralized resilient H_(∞)scheme is presented to design the state-feedback controllers with guaranteed H∞performance and resilience index based on a novel transmission interval-dependent loop functional method.When given the controllers,the proposed scheme can obtain a less conservative H_(∞)performance and resilience index that the LFC system can tolerate.The effectiveness of the proposed LFC scheme is evaluated on a one-area CPPS and two three-area CPPSs under DoS attacks.

A Triple Human-Digital Twin Architecture for Cyber-Physical Systems

With the development of information and communication technology and the advent of the Internet of Things(IoT)era,cyber-physical system(CPS)is becoming the trend of products or systems.The deep integration and real-time interaction between the physical world and the virtual world expand system functions.Although there are some CPS implementation guidelines,the virtual world is still relatively abstract compared to the concrete physical world that can be touched through the IoT.Besides that,human is a non-negligible CPS endogenous interactive intelligent component.In this paper,we propose a triple human-digital twin architecture,where the physical objects and the digital twins that are the projections of the physical entities establish the cornerstone of human functioning together.And the hierarchically distributed digital twins grow dynamically with the physical entities along the lifecycle.Furthermore,the interaction and collaboration among the physical objects,the digital twins,and the humans in their respective worlds(the expected world,the interpreted world,and the physical world)integrate the full value chain of the products in anticipation of seamless synergy.Finally,we present a power management digital companion platform for the lunar probe to demonstrate the efficacy of the architecture.

Topology-Based and Event-Oriented Approach to Simulation of Cyber-Physical Systems

A simulation model for cyber-physical systems(CPSs)was presented.The model was developed by the method of combination of topology-based and event-oriented that could be used to simulate systems with routing flexibility,service-selection flexibility and service- mode flexibility overall by integrating the strategies related.The validity of the model has been verified by two extensive experiments.

Guest Editorial for Special Issue on Cyber-Physical Systems

Ⅰ.Introduction CYBER-PHYSICAL system is a system of collaborating computational elements to control physical entities.The coordination and the tight link between computational,virtual and physical resources in cyber-physical system will have a pervasive effect on our everyday life.The development of cyber-physical system will create new opportunities for the introduction of services that will enhance the quality of life

Security and Privacy Challenges in Cyber-Physical Systems

Cyber-Physical Systems, or Smart-Embedded Systems, are co-engineered for the integration of physical, computational and networking resources. These resources are used to develop an efficient base for enhancing the quality of services in all areas of life and achieving a classier lifestyle in terms of a required service’s functionality and timing. Cyber-Physical Systems (CPSs) complement the need to have smart products (e.g., homes, hospitals, airports, cities). In other words, regulate the three kinds of resources available: physical, computational, and networking. This regulation supports communication and interaction between the human word and digital word to find the required intelligence in all scopes of life, including Telecommunication, Power Generation and Distribution, and Manufacturing. Data Security is among the most important issues to be considered in recent technologies. Because Cyber-Physical Systems consist of interacting complex components and middle-ware, they face real challenges in being secure against cyber-attacks while functioning efficiently and without affecting or degrading their performance. This study gives a detailed description of CPSs, their challenges (including cyber-security attacks), characteristics, and related technologies. We also focus on the tradeoff between security and performance in CPS, and we present the most common Side Channel Attacks on the implementations of cryptographic algorithms (symmetric: AES and asymmetric: RSA) with the countermeasures against these attacks.

From Mechatronic Components to Industrial Automation Things: An IoT Model for Cyber-Physical Manufacturing Systems

IoT is considered as one of the key enabling technologies for the fourth industrial revolution that is known as Industry 4.0. In this paper, we consider the mechatronic component as the lowest level in the system composition hierarchy that tightly integrates mechanics with the electronics and software required to convert the mechanics to intelligent (smart) object offering well defined services to its environment. For this mechatronic component to be integrated in the IoT-based industrial automation environment, a software layer is required on top of it to convert its conventional interface to an IoT compliant one. This layer, which we call IoT wrapper, transforms the conventional mechatronic component to an Industrial Automation Thing (IAT). The IAT is the key element of an IoT model specifically developed in the context of this work for the manufacturing domain. The model is compared to existing IoT models and its main differences are discussed. A model-to-model transformer is presented to automatically transform the legacy mechatronic component to an IAT ready to be integrated in the IoT-based industrial automation environment. The UML4IoT profile is used in the form of a Domain Specific Modelling Language to automate this transformation. A prototype implementation of an Industrial Automation Thing using C and the Contiki operating system demonstrates the effectiveness of the proposed approach.

Residual-Based False Data Injection Attacks Against Multi-Sensor Estimation Systems

This paper investigates the security issue of multisensor remote estimation systems.An optimal stealthy false data injection(FDI)attack scheme based on historical and current residuals,which only tampers with the measurement residuals of partial sensors due to limited attack resources,is proposed to maximally degrade system estimation performance.The attack stealthiness condition is given,and then the estimation error covariance in compromised state is derived to quantify the system performance under attack.The optimal attack strategy is obtained by solving several convex optimization problems which maximize the trace of the compromised estimation error covariance subject to the stealthiness condition.Moreover,due to the constraint of attack resources,the selection principle of the attacked sensor is provided to determine which sensor is attacked so as to hold the most impact on system performance.Finally,simulation results are presented to verify the theoretical analysis.