Cyber-Physical Systems Components Research Articles

Cyber-Physical Systems Technologies: Applications in Industry and Education

Industry 4.0 concept development forms new trends as cloud computing, big data analysis, the industrial internet of things, machine-to-machine technologies. Cyber-physical systems (CPS) paradigm is based on these trends and integrates of computation, networking and physical processes. Synergy Center at Peter the Great St. Petersburg Polytechnic University works in the areas of intelligent systems for data processing and control, motion control systems for robotics, complex automation and mechatronics as components of CPS.
 Keywords: Industry 4.0, Cyber-physical systems, Digital twin; intelligent control system, automation, Global digitalisation, Practical-oriented online courses, Skills training, Joint international educational programmes.

Perspective components of cyber-physical systems implementing conversion, coding data exchange, and user communication processes

Perspective components of cyber-physical systems implementing conversion, coding data exchange, and user communication processes

Cyber-Physical System Framework for Measurement and Analysis of Physical Activities

Several recent studies in Cyber-Physical Systems (CPS) focus on monitoring human movement and capturing data for further processing and analysis. However, there is a lack of studies that address the configurability and modularity of these systems, which is important for designing customized systems with customized devices. We propose a solution to solve this through a modular framework that automatically recognizes and configures new devices and provides real-time data wirelessly. The proposed framework creates a Digital Twin of the physical device and mirrors its attributes and sensory information into the cyber world so they can be used in real-time and post-routine analysis. As a proof of concept, a configurable CPS model for physical activities monitoring is designed and implemented. The designed gait monitoring and analysis system delivers spatiotemporal data from multiple multi-sensory devices to a central data handling and backup cloud server over conventional IEEE802.11 Wi-Fi. An experiment involving a young athlete examined whether or not the CPS components would recognize each other over foreign networks and communicate accurate information.

Software Safety Analysis with UML-Based SRBD and Fuzzy VIKOR- Based FMEA

Software often controls the behavior of mechanical and electrical systems, as well as interactions among their components in cyber-physical systems (CPS). The risks in CPS systems could result in losing tools, features, performance, and even life. Therefore, safety analysis for software in these systems is a highly critical and serious issue. The use of reliability block diagram is a method for checking the safety and reliability of systems. A reliability block diagram is a diagrammatic method for showing how component reliability contributes to the success or failure of a complex system. In this paper, a method for generating RBDs is presented analysis and demonstration of this method capability to evaluation of a software safety by use-case analysis, use-case diagram review, and use-case specification. Then, a Fuzzy VIKOR-based FMEA is used for further evaluation due to the presence of uncertain data. Finally, it is applied to a real CPS.

An Effective Security Requirements Engineering Framework for Cyber-Physical Systems

Context and motivation: Cyber-Physical Systems (CPSs) are gaining priority over other systems. The heterogeneity of these systems increases the importance of security. Both the developer and the requirement analyst must consider details of not only the software, but also the hardware perspective, including sensor and network security. Several models for secure software engineering processes have been proposed, but they are limited to software; therefore, to support the processes of security requirements, we need a security requirements framework for CPSs. Question/Problem: Do existing security requirements frameworks fulfil the needs of CPS security requirements? The answer is no; existing security requirements frameworks fail to accommodate security concerns outside of software boundaries. Little or even no attention has been given to sensor, hardware, network, and third party elements during security requirements engineering in different existing frameworks. Principal Ideas/results: We have proposed, applied, and assessed an incremental security requirements evolution approach, which configures the heterogeneous nature of components and their threats in order to generate a secure system. Contribution: The most significant contribution of this paper is to propose a security requirements engineering framework for CPSs that overcomes the issue of security requirements elicitation for heterogeneous CPS components. The proposed framework supports the elicitation of security requirements while considering sensor, receiver protocol, network channel issues, along with software aspects. Furthermore, the proposed CPS framework has been evaluated through a case study, and the results are shown in this paper. The results would provide great support in this research direction.

CPS data streams analytics based on machine learning for Cloud and Fog Computing: A survey

Cloud and Fog computing has emerged as a promising paradigm for the Internet of things (IoT) and cyber–physical systems (CPS). One characteristic of CPS is the reciprocal feedback loops between physical processes and cyber elements (computation, software and networking), which implies that data stream analytics is one of the core components of CPS. The reasons for this are: (i) it extracts the insights and the knowledge from the data streams generated by various sensors and other monitoring components embedded in the physical systems; (ii) it supports informed decision making; (iii) it enables feedback from the physical processes to the cyber counterparts; (iv) it eventually facilitates the integration of cyber and physical systems. There have been many successful applications of data streams analytics, powered by machine learning techniques, to CPS systems. Thus, it is necessary to have a survey on the particularities of the application of machine learning techniques to the CPS domain. In particular, we explore how machine learning methods should be deployed and integrated in Cloud and Fog architectures for better fulfilment of the requirements of mission criticality and time criticality arising in CPS domains. To the best of our knowledge, this paper is the first to systematically study machine learning techniques for CPS data stream analytics from various perspectives, especially from a perspective that leads to the discussion and guidance of how the CPS machine learning methods should be deployed in a Cloud and Fog architecture.

Использование вычислительных кластеров для обработки потоков пространственно-временных данных в информационно-измерительных системах

Geoinformation technologies are now becoming “end-to-end” technologies of the new digital economy. There is a need for solutions for efficient processing of spatial and spatio-temporal data that could be applied in various sectors of this new economy. Such solutions are necessary, for example, for cyberphysical systems. Essential components of cyberphysical systems are high-performance and easy-scalable data acquisition systems based on smart geosensor networks. This article discusses the problem of choosing a software environment for this kind of systems, provides a review and a comparative analysis of various open source software environments designed for large spatial data and spatial-temporal data streams processing in computer clusters. It is shown that the software framework STARK can be used to process spatial-temporal data streams in spatial-temporal data streams. An extension of the STARK class system based on the type system for spatial-temporal data streams developed by one of the authors of this article is proposed. The models and data representations obtained as a result of the proposed expansion can be used not only for processing spatial-temporal data streams in data acquisition systems based on smart geosensor networks, but also for processing spatial-temporal data streams in various purposes geoinformation systems that use processing data in computer clusters.

A PVS-Simulink Integrated Environment for Model-Based Analysis of Cyber-Physical Systems

This paper presents a methodology, with supporting tool, for formal modeling and analysis of software components in cyber-physical systems. Using our approach, developers can integrate a simulation of logic-based specifications of software components and Simulink models of continuous processes. The integrated simulation is useful to validate the characteristics of discrete system components early in the development process. The same logic-based specifications can also be formally verified using the Prototype Verification System (PVS), to gain additional confidence that the software design complies with specific safety requirements. Modeling patterns are defined for generating the logic-based specifications from the more familiar automata-based formalism. The ultimate aim of this work is to facilitate the introduction of formal verification technologies in the software development process of cyber-physical systems, which typically requires the integrated use of different formalisms and tools. A case study from the medical domain is used to illustrate the approach. A PVS model of a pacemaker is interfaced with a Simulink model of the human heart. The overall cyber-physical system is co-simulated to validate design requirements through exploration of relevant test scenarios. Formal verification with the PVS theorem prover is demonstrated for the pacemaker model for specific safety aspects of the pacemaker design.

Efficient and Scalable Runtime Monitoring for Cyber–Physical System

Our reliance on cyber–physical systems (CPSs) is increasingly widespread, but scalable methods for the analysis of such systems remain a significant challenge. Runtime verification of CPSs provides a reasonable middle ground between formal verification and simulation approaches, but it comes with its own challenges. A runtime verification system must run directly on the deployed application. In the CPS domain, it is therefore critical that a runtime verification system exhibits low overhead and good scalability so that the verification does not interfere with the analyzed CPS application. In this paper, we introduce Brace , a runtime verification system whose focus is on ensuring these performance qualities for applications in the CPS domain. Brace strives to bound the computation overhead for CPS runtime verification while preserving a high level of monitoring accuracy in terms of the number of false positive and false negative reports. Brace is particularly suitable to systems in which scheduling is distributed across networked CPS components. We evaluate Brace to determine how effectively and efficiently it can detect injected errors in two existing real-life CPS applications with distributed scheduling. Our results demonstrate that Brace efficiently detects those errors and a few true bugs and is able to bound both the memory and computation overhead even in systems with large numbers of observed events.

A Monte Carlo-based exploration framework for identifying components vulnerable to cyber threats in nuclear power plants

With the extensive use of digital Instrumentation and Control (I&C) systems, Nuclear Power Plants (NPPs) are becoming Cyber-Physical Systems (CPSs). Their integrity can, then, be compromised also by security breaches (such as cyber attacks). Multiple failure modes (such as bias, drift and freezing) can occur, both due to random failures or induced by malicious external attacks. In this paper, we illustrate an exploration approach that, based on safety margins estimation, allows identifying the most vulnerable components to malicious external attacks. For demonstration, we apply the approach to the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED). Its object-oriented model is embedded within a Monte Carlo (MC)-driven engine that injects different types of cyber attacks at random times and magnitudes. Safety margins are, then, calculated and used for identifying the most vulnerable CPS components. This allows selecting protections to make ALFRED resilient towards maliciously induced failures.

Cyber-Physical Systems Security—A Survey

With the exponential growth of cyber-physical systems (CPS), new security challenges have emerged. Various vulnerabilities, threats, attacks, and controls have been introduced for the new generation of CPS. However, there lack a systematic study of CPS security issues. In particular, the heterogeneity of CPS components and the diversity of CPS systems have made it very difficult to study the problem with one generalized model. In this paper, we capture and systematize existing research on CPS security under a unified framework. The framework consists of three orthogonal coordinates: (1) from the \emph{security} perspective, we follow the well-known taxonomy of threats, vulnerabilities, attacks and controls; (2)from the \emph{CPS components} perspective, we focus on cyber, physical, and cyber-physical components; and (3) from the \emph{CPS systems} perspective, we explore general CPS features as well as representative systems (e.g., smart grids, medical CPS and smart cars). The model can be both abstract to show general interactions of a CPS application and specific to capture any details when needed. By doing so, we aim to build a model that is abstract enough to be applicable to various heterogeneous CPS applications; and to gain a modular view of the tightly coupled CPS components. Such abstract decoupling makes it possible to gain a systematic understanding of CPS security, and to highlight the potential sources of attacks and ways of protection.

Dynamic Defense Resource Allocation for Minimizing Unsupplied Demand in Cyber-Physical Systems Against Uncertain Attacks

Cyber-attacks in cyber-physical systems (CPS) are receiving much attention due to the pervasive use of communication in essential services. If cyber components in CPS are compromised by attackers, the ability to maintain stability of the physical system is lost, and performance disruptions may occur. Vulnerability analysis allows quantifying the impact of attacks based on the damage cost model. Yet, existing works partially account for uncertainties in cyber-attacks and may provide inadequate support to decision making. This paper proposes a framework for optimal defense resource allocation for minimizing unsupplied demand of CPS under uncertain cyber-attacks. The vulnerability model of cyber components is described by an attacker–defender two-stage min–max game. The unavailability of cyber components causes the loss of performance of the monitored physical components. Uncertainties in the most probable attack time and in the accuracy of its estimate by the defender are considered. Numerical studies identify the optimum strategies in terms of protection and redundancy allocation of cyber components, and demonstrate that the contest intensity largely affects the two-stage game. Furthermore, if uncertainties increase, the system damage costs also increase and the defensive resource allocation strategies converge to a constant one due to the defender's lack of information about the attack.

SFTA-Based Approach for Safety/Reliability Analysis of Operational Use-Cases in Cyber-Physical Systems

The software is often responsible for controlling the behavior of mechanical and electrical components, as well as interactions among these components in cyber-physical systems (CPS). The risks in CPS systems could result in losing tools, features, performance and even life. Therefore, safety analysis for software in these systems is a highly critical and serious issue. In general, safety and reliability approaches play a major role in a risk management process in CPS. In this paper, after reviewing the major techniques of software reliability and safety in CPS, an software fault tree analysis (SFTA)-based approach is presented for analysis of operational use-cases (UC) in a CPS system. In our approach, the events related to use-cases are extracted, and the related SFTA is then obtained using the proposed algorithm. Moreover, a semi-automatic method is presented in this paper to produce software failure mode and effects analysis (SFMEA) from SFTA. The results of our approach are applicable for software safety analysis in a real CPS system, including the control system of Iranian National Observatory telescope. Assessment of the suggested method is performed through numerous safety/reliability criteria and the qualitative/quantitative analysis based on these criteria.

XCPS

Cyber-Physical Systems (CPS) play an important role in the modern high-tech industry. Designing such systems is an especially challenging task due to the multi-disciplinary nature of these systems, and the range of abstraction levels involved. To facilitate hands-on experience with such systems, we develop a cyber-physical platform that aids in both research and education on CPS. This paper describes this platform, which contains all typical CPS components. The platform is used in various research and education projects for bachelor, master, and PhD students. We discuss the platform and illustrate its use with a number of projects and the educational opportunities they provide.

Security and networking for cyber‐physical systems

Cyber-physical systems (CPS) are emerging research areas that involve multiple disciplines. Two critical components in CPS are networking technologies and security. Because of the multi-disciplinary nature, the networking and security of CPS expand beyond traditional computing domains and have to consider the impact of applied physical systems. Therefore, new innovations are required such as novel transmission technologies, networking protocols, architectures, and security solutions. As a result, a significant amount of research work is expected for new models, performance analysis as well as evaluation, prototypes, and testbeds. This special issue focuses on research interests and activities related to networking and security in SmartGrid, Transportation and Medical Systems, with an emphasis on original analytical, experimental, and systems-related papers in these target domains. After a very careful review of the many highly qualified submissions, the editorial committee accepted a total of nine papers into this special issue. Among these, three papers are related to SmartGrid security, two relating to CPS security-driven wireless communication, three relating to CPS wireless backbone architectures and protocols, and one relating to medical system security. In SmartGrid security, Baumeister and Dong propose a security identity management solution for SmartGrid. Another work by Wen et al. designs a credit-based incentive tariff scheme. Yang, Chang, and Yu develop a solution to identify false data injection attack in power system. In security-driven CPS wireless communications, Si, Sun, and Zhang propose a solution to dynamically manage wireless spectrum based on quality of service and security to improve transportation CPS surveillance. The paper by An et al. integrates vulnerability into minimum cost-based wireless routing for sensor CPS. Kanjee and Liu propose a solution to relay-based authentication solution for medical systems. In wireless architectures and protocols, Yang et al. design a location-aware routing for vehicular CPS, Wang et al. develop a solution to collaborative measurement on network traffic that is friendly to transmission control protocol rate control protocols. Bhandare et al. evaluate the collision avoidance performance in wireless ad hoc backbone for CPS systems. On behalf of the editorial committee, we express our sincere thanks to all authors and reviewers for their significant contribution to this special issue. We are also grateful to Editors-in-Chief Drs. Chen Hsiao Hwa and Hamid R. Sharif and to the editorial staff for their excellent help and assistance. Without their contributions, it would have been impossible to produce this special issue. We hope that this special issue will inspire interested scholars to get involved in this promising and active research area.

Definitions of predictability for Cyber Physical Systems

With the recent proliferation of different types of Cyber Physical Systems (CPS), it is critically important to investigate the predictability of such systems. Along with functional correctness of the components, these systems must also ensure that timing and delay constraints of components are properly for the entire system to behave in a predictable manner in presence of various kinds of uncertainties. While the functional correctness of the CPS components has been investigated in the past, very little is available about the timing issues. The objective of this paper is to conduct an investigation of key issues involved to ensure the predictability of the system, introduce rigorous definitions of performance parameters, and propose metrics for their evaluation and analyze their suitability to be used in the presence of uncertainties in which CPS operate. The results are expected to provide greater insight into the time critical behavior of CPS components.

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.

Runtime Monitoring of Cyber-Physical Systems Under Timing and Memory Constraints

The goal of runtime monitoring is to inspect the well-being of a system by employing a monitor process that reads the state of the system during execution and evaluates a set of properties expressed in some specification language. The main challenge in runtime monitoring is dealing with the costs imposed in terms of resource utilization. In the context of cyber-physical systems, it is crucial for a software monitoring solution to be time predictable to improve scheduling, as well as support composition of monitoring solutions with an overall predictable behavior. Moreover, a small memory footprint is often required in components of cyber-physical systems, especially in deeply embedded systems. In this article, we propose a novel control-theoretic software monitoring solution for coordinating time predictability and memory utilization in runtime monitoring of systems that interact with the physical world. The controllers attempt to reduce monitoring jitter and maximize memory utilization while simultaneously ensuring the soundness of evaluation of properties. For systems where multiple properties are required to be monitored simultaneously, we construct a buffer sharing mechanism in which controllers dynamically share the memory space to negate the effect of bursts of environment actions, thus reducing jitter due to transient high loads. To validate our design choices, we present three case studies: (1) a Bluetooth mobile payment system, which shows a sporadic rate of events during peak hours; (2) a laser beam stabilizer for target tracking, and (3) a monitoring system for air/fuel ratio in a car engine exhaust and the CAM inlet position in the engine’s cylinders. The experimental results of the case studies demonstrate up to 40% improvement in time predictability of the monitoring solution when compared to a basic event-triggered approach. Moreover, memory utilization reaches an average of 90% when using our dynamic buffer resizing mechanism.

A standardized design methodology for complex digital logic components of cyber-physical systems

As an important part of cyber-physical systems, the digital logic system’s complexity are rapidly increasing, and its design flows become more and more tedious. A modeling and verification methodology for complex digital logic components is presented to improve the development quality and efficiency. In order to help developer to understand the design intent preferably and speed up the development process, design activities are carried out under a convenient modeling methodology and a precise verification solution for completing the design cycle. Its calculus system offers a theoretic way to connect components via connectors, and then provides a theoretical basis for further verification. A washing machine controller design shows that the modeling can reflect the design intent of the designers effectively, detect some design errors which maybe result in modeling failures in implementation as soon as possible, and avoid the negligence and errors in modeling for complex digital systems.

A co-simulation framework for design of time-triggered automotive cyber physical systems

Designing cyber-physical systems (CPS) is challenging due to the tight interactions between software, network/platform, and physical components. Automotive control system is a typical CPS example and often designed based on a time-triggered paradigm. In this paper, a co-simulation framework that considers interacting CPS components for assisting time-triggered automotive CPS design is proposed. Virtual prototyping of automotive vehicles is the core of this framework, which uses SystemC to model the cyber components and integrates CarSim to model the vehicle dynamics. A network/platform model in SystemC forms the backbone of the virtual prototyping. The network/platform model consists of processing elements abstracted by real-time operating systems, communication systems, sensors, and actuators. The framework is also integrated with a model-based design tool to enable rapid prototyping. The framework is validated by comparing simulation results with the results from a hardware-in-the-loop automotive simulator. The framework is also used for design space exploration (DSE).