A holonic-based method for design process of cyber-physical reconfigurable systems

Cyber Physics Systems consists of physical systems and information systems. Modern power systems are increasingly dependent on information systems, experts and scholars are paying more and more attention to cyber attacks on CPS. This paper first introduces the existing research on cyber physical power system. Then this paper reviews the current status of existing cyber attacks. Finally, the modeling method for CPS is summarized such as correlation characteristic matrix, graph theory, complex network theory, finite state machine, mathematical programming and cellular automata method. These methods have vital theoretical and practical significance for the research of cyber physical power system.

Security and Privacy Aspect of Cyber Physical Systems

Cyber-physical production systems are highly flexible systems that enable adaptive production processes. In these systems, all participants of the production process possess individual information about themselves and are equipped with sensors, actors, and communication interfaces. They can interact with each other and autonomously develop and execute process relevant decisions. For each component, a standard process sequence and alternative process sequences are defined. If a deviation in the standard process occurs during the production of an individual component, the process participants can interact with each other and autonomously define an appropriate response strategy and execute it by using actors of the participants and the intralogistics. Regardless of the deviation, the manufacturing and assembly process of individual components in cyber-physical production systems can still proceed. For this purpose, process deviations and the response behavior of cyber-physical production systems are analyzed, modeled, and simulated, to illustrate the benefits of cyber-physical production systems and to develop a process deviation management system for actual, physical production systems based on cyber-physical systems.

Cyber Physical Systems (CPS) are redefining modern engineering practices by bringing the computational systems together with physical processes, boosting efficiency, security, and sustainability in different industries. This research highlights the influence of CPS in different sectors: its power to facilitate realtime decision making, predictive maintenance, and cybersecurity issues. The context in which this study occurs is to the application of digital twin technology in CPS — which is physical systems’ simulation for performance optimization and downtime reduction. The research includes the analysis of the efficiency of cybersecurity measures applied in CPS environment, the identification of vulnerabilities, and the suggestions of solutions for the mitigation of a cyber threat. Digital twins and predictive maintenance appears to improve the system performance by 30%, reduces the downtime by 25% due to application. Moreover, the research addresses upcoming concerns of sustainable practices in CPS and emerging technologies such as Industry 4.0 that promote resource optimization and waste reduction. The results show that CPS can improve both the operational efficiency and the environmental sustainability by enabling a smarter resource management. This work advances our understanding of trends, challenges and future directions in CPS as a means to inform engineering management practices, which are enabled by CPS.

Recent developments in the field of cyber physical systems (CPS) and internet of things (IoT) open up new possibilities in manufacturing. CPS and IoT represent enabling means for facilitating the companies’ adaptation to the ever-changing market needs and adoption of individualized manufacturing paradigm. It is foreseen that implementation of CPS and IoT will lead to new industrial revolution known as Industry 4.0. The fourth industrial revolution will bring about the radical changes in manufacturing process control through distribution of control tasks to intelligent devices. On the other hand, over the last decades International Electrotechnical Commission invested significant efforts in generation of the standard IEC 61499 for distributed automation systems. In this paper we provide the outline of the interconnection of IEC 61499 standard and Reference Architecture Model Industrie 4.0 in cyber physical production systems. The findings of the paper are illustrated using a realistic case study—an example of pneumatic manipulator that is made of CPS devices.

Cyber Physical Systems (CPSs) are both software and hardware intense systems which are integrated into the digital world. An increasingly relevant application area for CPSs are software-driven industrial Production Automation Systems. A major driver of these Cyber Physical Production Systems is the need to integrate intelligent and smart functionalities into the production process at runtime that can run in the cyber world and do not radically change the underlying control flow of the physical plant. To gather the necessary knowledge for smart functionalities both cyber and physical parts must be captured, kept and analyzed together in a suitable CPS architecture – also despite frequent evolutionary changes during their whole (usually relative long) life span. This paper addresses this problem by presenting a service-component architecture for smart service-oriented CPSs which can manage implicit knowledge by acquiring, handling and analyzing domain specific service-components with respect to the CPS context.

A Through Analysis on Protecting Cyber Threats and Attacks on Cps Embedded Subsystems

CPS is complex distributed systems, which contain computing, communications, and control. CPS is a product of the combination of physical world and the cyber world. The cyber world needs a lot of physical equipment to deal with perception and communication, then collect and transfer the information in the real environment, and by computation to forecast what might happen in future real environment, at last through the control strategy to achieve the optimal solution. In short, cyber physical system is the complex systems combination with computation system, sensory system and control system. Cyber physical system through more extensive connection, the physical world more thorough cognition, more effectively control the physical world, make the information world and the physical world closer integration, realize coordination awareness and control of the physical world. The paper through the analysis of the human perception system, build a cyber-physical fusion system based on human perception architecture.

Cyber Physical Systems (CPS) are characterized by their ability to integrate\nthe physical and information or cyber worlds. Their deployment in critical\ninfrastructure have demonstrated a potential to transform the world. However,\nharnessing this potential is limited by their critical nature and the far\nreaching effects of cyber attacks on human, infrastructure and the environment.\nAn attraction for cyber concerns in CPS rises from the process of sending\ninformation from sensors to actuators over the wireless communication medium,\nthereby widening the attack surface. Traditionally, CPS security has been\ninvestigated from the perspective of preventing intruders from gaining access\nto the system using cryptography and other access control techniques. Most\nresearch work have therefore focused on the detection of attacks in CPS.\nHowever, in a world of increasing adversaries, it is becoming more difficult to\ntotally prevent CPS from adversarial attacks, hence the need to focus on making\nCPS resilient. Resilient CPS are designed to withstand disruptions and remain\nfunctional despite the operation of adversaries. One of the dominant\nmethodologies explored for building resilient CPS is dependent on machine\nlearning (ML) algorithms. However, rising from recent research in adversarial\nML, we posit that ML algorithms for securing CPS must themselves be resilient.\nThis paper is therefore aimed at comprehensively surveying the interactions\nbetween resilient CPS using ML and resilient ML when applied in CPS. The paper\nconcludes with a number of research trends and promising future research\ndirections. Furthermore, with this paper, readers can have a thorough\nunderstanding of recent advances on ML-based security and securing ML for CPS\nand countermeasures, as well as research trends in this active research area.\n

Cyber-physical systems (CPS) are considered the integration of physical systems in the real world and control software in computing systems. In CPS, the real world and the computing systems are connected through networks with real-time information exchange. The introduction of networking technologies in CPS has substantial advantages in terms of system efficiency, scalability, maintenance, and many more. However, CPS are vulnerable to malicious attackers intruding on the network. The attackers aim to destroy the physical systems with cyber-physical attacks, in which the main objective is to remotely cause malfunctions in physical systems through networks. Therefore, extensive research on cyber-physical security has been conducted to detect cyber-physical attacks and guarantee the stability of the physical systems under cyber-physical attacks. In this survey, we conduct an exhaustive review of the literature on threats to CPS and on resilient CPS design strategies. First, we discuss the structure of CPS, considering physical dynamics, computing systems, and networks. Then, we provide a taxonomy of cyber-physical attacks with three properties (attack space, attack location, and stealthiness). These three attributes represent the requirements for the implementation of cyber-physical attacks. We review existing studies on anomaly-detection strategies against cyber-physical attacks in terms of physics, networks, and machine learning techniques. Moreover, we analyze the impact of typical cyber-physical attacks and the constraints on attack implementations. In particular, for each of the well-established cyber-physical attacks, we present numerical examples that clearly illustrate the time responses of the physical systems with a conventional physics-based anomaly detector. We also review advances in the typical cyber-physical attacks and the detection methods for these attacks. Furthermore, we review resilient CPS designs in the context of control theory, network management, and data-driven technologies. We conclude the survey by identifying future research directions.

For implementation of Cyber-Physical Systems (CPS) simulation, interoperability between physical and cyber system are required. IEEE High Level Architecture (HLA) is standard for distributed simulation interoperability, and ETSI Machine-to-Machine (M2M) is standard for integration between physical machines. In this paper, we propose M2MHLA adaptor to integrate HLA-based simulations and M2M physical machines. M2M-HLA adaptor is located between HLA simulation systems and M2M systems. This adaptor transforms HLA data to M2M data and M2M data to HLA data. We propose sequence structure between M2M-HLA APIs for interconnection, data type definition and transformation method and time management method for design and implementation M2M-HLA adaptor. Because of M2M-HLA adaptor allows interoperability between different cyber systems and physical systems, this would extend the scope of CPS simulation system and increase its utilization.

Reliability assessment of a power system with cyber-physical interactive operation of photovoltaic systems

Construction of approximate reasoning model for dynamic CPS network and system parameter identification

Industry 4.0 denotes a recent trend that aims at exploiting Cyber Physical Systems (CPS), based on IoT (Internet of Things) and cloud computing technologies, to obtain increased degrees of cooperation and communication in production systems, thus leading to what is referred to as Cyber Physical Production Systems (CPPS) or “Smart Factories”.

Cloud computing and its related virtualization technologies have become one of dominant trends to deploy software, compute difficult problems, store different types of data, and stream real-time video and audio. Due to its benefits from cost-efficiency and scalability to maintain server solutions, many organizations are migrating their server applications running on physical servers to virtual servers in cloud computing infrastructures. Moreover, cloud computing has enabled mobile and battery-powered devices to operate without strong processing power and large storage capacity. However, it is not trivial to use this trendy technology for medical Cyber Physical Systems (CPSs) which require processing tasks’ requests to send instructions to the local actuator within specified deadlines. Since a medical CPS device monitoring a patient’s vital signs may not have a second chance to recover from an erroneous state, achieving cost-efficiency with higher resource utilization in cloud computing may not be the ultimate goal to configure the healthcare IT infrastructure with medical CPS devices. In this paper, we focus on private cloud infrastructures with the fair resource sharing mechanism in order to run medical CPS applications. First, we introduce our medical CPS device model used for designing our cloud infrastructure following the Integrated Clinical Environment (ICE) standard developed by the Medical Device Plug-and-Play (MDPnP) project. Second, we investigate limitations to deploy CPS applications using existing auto-scaling mechanisms. Finally, we propose our novel middleware with a virtual resource sharing mechanism inspired by autonomic computing, and present its performance evaluation results simulated in the OpenStack private cloud.