Resource-Aware Control and Dynamic Scheduling in CPS

Security and Privacy Aspect of Cyber Physical Systems

Cyber-Physical System (CPS) is a symbol of the fourth industrial revolution (4IR) by integrating physical and computational processes which can associate with humans in various ways. In short, the relationship between Cyber networks and the physical component is known as CPS, which is assisting to incorporate the world and influencing our ordinary life significantly. In terms of practical utilization of CPS interacting abundant difficulties. Currently, CPS is involved in modern society very vastly with many uptrend perspectives. All the new technologies by using CPS are accelerating our journey of innovation. In this paper, we have explained the research areas of 14 important domains of Cyber-Physical Systems (CPS) including aircraft transportation systems, battlefield surveillance, chemical production, energy, agriculture (food supply), healthcare, education, industrial automation, manufacturing, mobile devices, robotics, transportation, and vehicular. We also demonstrated the challenges and future direction of each paper of all domains. Almost all articles have limitations on security, data privacy, and safety. Several projects and new dimensions are mentioned where CPS is the key integration. Consequently, the researchers and academicians will be benefited to update the CPS workspace and it will help them with more research on a specific topic of CPS. 158 papers are studied in this survey as well as among these, 98 papers are directly studied with the 14 domains with challenges and future instruction which is the first survey paper as per the knowledge of authors.

Guest Editorial

This paper addresses the problem of devising an effective information fusion architecture for a task scheduling algorithm which facilitates data processing of a Cyber Physical System (CPS) under bounded latency for bursty or lossy traffic. Task scheduling traditionally caters to real-time systems where a feedback loop does not exist allowing the serviced application to be independent of the inputs from the server. However, owing to the nature of a near real-time CPS, such liberties cannot be entertained. Additionally, the advent of big data in CPS has necessitated the use of Cloud Computing as a scalable and cost effective alternative. Task scheduling in such CPSs, where inputs from the Cloud complete the feedback loop is a major research issue. Therefore, in this paper, we propose a multi-layered information fusion architecture which integrates such a task scheduling mechanism by accommodating both traffic bursts and packet losses. Our scheduling algorithm ensures that the overall latency always remains under an acceptable upper bound as required by the CPS application.

Cyber physical systems (CPS) is the integration of three processes: physical process, communication process and computation process. Due to the high demand of safety and real- time feature, CPS requires massive real-time spatial and temporal messages. Therefore, representation and demonstration of spatio- temporal information is vital in every stage, such as specification, design, operation, control, and supervision of CPS. In this paper, we propose a method combining clock theory and RCC-8 together indicating spatio-temporal information of CPS, and we present spatio-temporal sequence diagram for change tracking under the specific scene. We take vehicle system as instance to see how the method work in description of spatio-temporal information between vehicles and vehicles, vehicles and people, vehicle and surroundings in different situations.

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

One of the most significant directions in the development of computer science and information and communication technologies is represented by Cyber-Physical Systems (CPS) which are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at the same time, data-accessing and data-processing services available on the internet. Cyber-Physical Production Systems (CPPS), relying on the newest and foreseeable further developments of computer science, information and communication technologies on the one hand, and of manufacturing science and technology, on the other, may lead to the 4th Industrial Revolution, frequently noted as Industrie 4.0. The paper underlines that there are significant roots generally – and particularly in the CIRP community – which point towards CPPS. Expectations and the related new R&D challenges are also outlined.

Cyber-physical Systems (CPS) combine human-machine interaction, the physical world around us, and software aspects by integrating physical systems with communication networks. Opportunities and research challenges are largely interconnected with the three core sub-domains of CPS m computation, communication and control. The current state of the art of the legacy communication technology is one of the major hindrances limiting the evolution of CPS. Most specifically, innovation in communication is restricted with existing routing and switching technologies leaving no practical methods for researchers to test their new ideas. Software Defined Networking (SDN), through the realization of OpenFlow, separates network control logic from the underlying physical routers and switches. This phenomenon allows researchers to write high-level control programs specifying the behavior of the core networks used to implement CPS and thus, enable innovation in next generation communication architectures for CPS. In this paper, we propose a SDN architecture for industrial automation. Network design requirements are extracted from formal component specifications which support the generation of automatic network configurations. The proposed SDN architecture aims to leverage Industry 4.0 and Smart Factories, to bring together industrial automation installations with networking and Internet technologies.

In this work, we focus on securing cyber-physical systems (CPS) in the presence of network-based attacks, such as Man-in-the-Middle (MitM) attacks, where a stealthy attacker is able to compromise communication between system sensors and controllers. Standard methods for this type of attacks rely on the use of cryptographic mechanisms, such as Message Authentication Codes (MACs) to ensure data integrity. However, this approach incurs significant computation overhead, limiting its use in resource constrained systems. Consequently, we consider the problem of scheduling multiple control tasks on a shared processor while providing a suitable level of security guarantees. Specifically, by security guarantees we refer to control performance, i.e., Quality-of-Control (QoC), in the presence of attacks. We start by mapping requirements for QoC under attack into constraints for security-aware control tasks that, besides standard control operations, intermittently perform data authentication. This allows for the analysis of the impact that security-related computation overhead has on both schedulability of control tasks and QoC. Building on this analysis, we introduce a mixed-integer linear programming-based technique to obtain a schedulable task set with predefined QoC requirements. Also, to facilitate optimal resource allocation, we provide a method to analyze interplay between available computational resources and the overall QoC under attack, and show how to obtain a schedulable task set that maximizes the overall QoC guarantees. Finally, we prove usability of our approach on a case study with multiple automotive control components.

Cyber-physical systems (CPSs), which integrate sensing, computation, and control, are widely deployed in safety-critical applications such as industrial monitoring and predictive maintenance. Industrial fault diagnosis systems (IFDSs), as a representative CPS, enable intelligent health monitoring but are increasingly vulnerable to stealthy adversarial attacks—carefully crafted input perturbations that mislead models while remaining imperceptible. These attacks compromise system safety, highlighting the urgent need for learning-based security control in CPS. This article proposes multilayered noisy mixup (MLNM)-frequency shift (FrSh), a theoretically grounded adversarial defense framework for IFDS under real-world conditions involving nonstationary signals and class imbalance. The framework integrates two components: multilayered noisy mixup (MLNM) and frequency shift (FrSh). MLNM injects structured additive and multiplicative noise during training and is theoretically proven to introduce first- and second-order regularization terms in the loss function, enhancing generalization and gradient stability. FrSh performs spectrum-aware transformations that preserve conjugate symmetry and spectral integrity, with formal guarantees of aliasing-free, reversible frequency mapping, facilitating effective learning of high-frequency diagnostic features. Extensive experiments on benchmark datasets demonstrate that MLNM-FrSh significantly improves adversarial robustness and standard accuracy compared to state-of-the-art baselines. This work contributes a reliable and theoretically principled solution for attack-resilient fault diagnosis, advancing the broader goal of intelligent security control in 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.

Automation and the digital transformation have become important factors in the energy sector, as modern energy systems increasingly rely on communication and information technology to combine smart controls with hardware infrastructure. With the emergence of cyber-physical systems (CPS) as a trans-disciplinary field, such modern energy systems can be classified as cyber-physical energy systems (CPES), integrating the related research and development within a broader scope. An important aspect of the research and development related to CPS is to bridge the gap between the traditional engineering domains and computer science. This is especially true for CPES, where the related engineering domains have in the past come up with proven and reliable methods for designing even large and complex systems. However, existing modeling and simulation tools still struggle to cover all aspects of CPES. Hence, a combination of universal modeling languages and established, domain-specific tools (such as grid simulators and telecommunication simulators) is necessary. New methods, tools and algorithms are needed that are compact, computationally inexpensive, potentially self-organizing and intrinsically stable if applied to real energy systems.

In a time when technology changes continuously, where things you need today to run a certain system, might not be needed tomorrow anymore, security is a constant requirement. No matter what systems we have, or how we structure them, no matter what means of digital communication we use, we are always interested in aspects like security, safety, privacy. An example of the ever-advancing technology are cyber-physical systems. We propose a complex security architecture that integrates several consecrated methods such as cryptography, steganography and digital signatures. This architecture is designed to not only ensure security of communication by transforming data into secret code, it is also designed to control access to the system and detect and prevent cyber attacks.

With the increasing dependencies on Information and Communication Technologies (ICTs), the smart distribution system has similar characteristics to Cyber-Physical System (CPS) and is seen as the so-called “cyber-physical power system” (CPPS). However, the impact of upstream substation is becoming one of the main factors impacting on distribution reliability. To avoid the too optimistic conclusion, the Cyber-Induced Dependent Failures (CDFs) of upstream substation are important to be considered. Thus the cyber security risk brought by both the malfunction of ICT components and the cyber-attack should be taken into account. This paper provided a methodology to incorporate both the two sides of CDFs in upstream substation into cyber-enabled distribution system reliability assessment. In the sequential Monte Carlo simulation (MCS), the game process between attackers and defenders can be modelled as the semi-Markov Chain (SMP), and indices are calculated by the minimal path method. The effects of CDFs are quantified and converted onto the joint feeders, based on the Breadth-First-Search (BFS), as well. Some conclusions for the distribution and substation automation planning have been made and verified by the cyber-extended Roy Billinton Test System (RBTS).

In the real-time task scheduling of Cyber Physical System (CPS), the existing scheduling algorithms can’t effectively differentiate the importance level of random tasks, resulting in poor real-time scheduling of important random tasks and insufficient submission rate. This paper comprehensively considers the factors of recent available time, criticality and execution time, and then proposes a fuzzy scheduling algorithm of high priority random tasks (FSA-HPRT) for CPS. The algorithm first obtains the applicable time slice by maximizing delayed the execution time of the periodic task, and calculates the difference between the end time of the periodic task and the deadline time as the error time slice. Then use the fuzzy set to process the latest available time, criticality and execution time of the random task to decide the random task priority. Finally, the task-scheduling queue is established for the system to perform scheduling according to the priority of the random task by using the applicable time slice and the error time slice. The simulation results show that compared with the ISS algorithm, the proposed algorithm can significantly improve the submission rate of important random tasks. At the same time, high-priority random tasks can get responses preferentially.