Challenges In Cyber-physical Systems Research Articles

A novel adaptive sampling algorithm for cyber-physical systems

AbstractSensors are the main components in Cyber-Physical Systems (CPS), which transmit large amounts of physical values and big data to computing platforms for processing. On the other hand, the embedded processors (as edge devices in fog computing) spend most of their time reading the sensor signals as compared with computing time. The impact of sensors on the performance of fog computing is very great, thus, the enhancement of the reading time of sensors will positively affect the performance of fog computing, and solves the CPS challenges such as delay, timed precision, temporal behavior, energy, and cost. In this paper, we propose an algorithm based on the 1st derivative of the sensor signal to generate an adaptive sampling frequency. The proposed algorithm uses an adaptive frequency to capture the sudden and rapid change in sensor signal in the steady state. Finally, we realize and tested it using the Ptolemy II Modeling Environment.

Security enhancement of cyber-physical system using modified encryption AESGNRSA technique

<span>A cyber-physical system (CPS) is a combination of physical components with computational elements to interact with the physical world. The integration of these two systems has led to an increase in security concerns. Traditional encryption algorithms designed for general-purpose computing environments may not adequately address the distinct challenges of CPS, such as limited processing power, delay, and resource-constrained hardware. Therefore, there is a pressing need to develop an encryption algorithm that is optimized for CPS security without compromising the critical real-time aspects of these systems. This research has designed a modified encryption technique named the advanced encryption standard in galois counter mode with nonce and rivest-shamir-adleman algorithm (AESGNRSA). A smart medical system is designed to monitor the health of remotely located patients. The AESGNRSA algorithm is applied to the three servers of this system. The data of 1.5 lakh patients is fed to this system to verify the effectiveness of the AESGNRSA algorithm. The performance parameters like encryption and decryption time, encryption and decryption throughput, and encrypted file size are calculated for the AESGNRSA algorithm. The comparative analysis proved that AESGNRSA has the highest performance as compared to other algorithms and it can protect CPS against many cyber-attacks.</span>

Securing Secrets in Cyber-Physical Systems: A Cutting-Edge Privacy Approach with Consortium Blockchain.

In the era of interconnected and intelligent cyber-physical systems, preserving privacy has become a paramount concern. This paper aims a groundbreaking proof-of-concept (PoC) design that leverages consortium blockchain technology to address privacy challenges in cyber-physical systems (CPSs). The proposed design introduces a novel approach to safeguarding sensitive information and ensuring data integrity while maintaining a high level of trust among stakeholders. By harnessing the power of consortium blockchain, the design establishes a decentralized and tamper-resistant framework for privacy preservation. However, ensuring the security and privacy of sensitive information within CPSs poses significant challenges. This paper proposes a cutting-edge privacy approach that leverages consortium blockchain technology to secure secrets in CPSs. Consortium blockchain, with its permissioned nature, provides a trusted framework for governing the network and validating transactions. By employing consortium blockchain, secrets in CPSs can be securely stored, shared, and accessed by authorized entities only, mitigating the risks of unauthorized access and data breaches. The proposed approach offers enhanced security, privacy preservation, increased trust and accountability, as well as interoperability and scalability. This paper aims to address the limitations of traditional security mechanisms in CPSs and harness the potential of consortium blockchain to revolutionize the management of secrets, contributing to the advancement of CPS security and privacy. The effectiveness of the design is demonstrated through extensive simulations and performance evaluations. The results indicate that the proposed approach offers significant advancements in privacy protection, paving the way for secure and trustworthy cyber-physical systems in various domains.

A Centralized MongoDB-Based Repository Design for IIoT Data: The ecoKI Project*

One of the challenges of cyber-physical systems is the data acquisition in real- time through different communication protocols within the scope of the Industrial Internet of Things (IIoT). This IIoT data is mainly specified as big in amount, continuous in nature, unstructured, and ambiguous format. It is also enigmatic in terms of structure for an overview of the manufacturing plant and which data belongs to which sensor or machine. Presently, relational database technologies are inadequate to cater to such kinds of IIoT data due to their strict data structure and relations. For this reason, we presented the ontology-based data repository model implementation for the process industry using MongoDB, which is a cross- platform document-oriented, most sought-after ample data storage database system nowadays. Firstly, we have designed a JSON-based data-model schema for the IIoT data repository, which gathers the data with the help of one of the most commonly used communication protocols within the scope of IIoT, OPC UA. Secondly, our schema stores the meta-data and data using embedded referencing through the same data-model. Hence, the scalability, flexibility, and variety of the data storage system have increased. Lastly, with the execution of insertion and search queries, we show how fast to get the desired data element hierarchy or track any particular data, which becomes possible due to the proposed ontology. This effectiveness of the ontology-based data-model also minimize the overhead of the machine learning engineer job.

Adopting microservices and DevOps in the cyber‐physical systems domain: A rapid review and case study

AbstractThe domain of cyber‐physical systems (CPS) has recently seen strong growth, for example, due to the rise of the Internet of Things (IoT) in industrial domains, commonly referred to as “Industry 4.0.” However, CPS challenges like the strong hardware focus can impact modern software development practices, especially in the context of modernizing legacy systems. While microservices and DevOps have been widely studied for enterprise applications, there is insufficient coverage for the CPS domain. Our goal is therefore to analyze the peculiarities of such systems regarding challenges and practices for using and migrating towards microservices and DevOps. We conducted a rapid review based on 146 scientific papers, and subsequently validated our findings in an interview‐based case study with nine CPS professionals in different business units at Siemens AG. The combined results picture the specifics of microservices and DevOps in the CPS domain. While several differences were revealed that may require adapted methods, many challenges and practices are shared with typical enterprise applications. Our study supports CPS researchers and practitioners with a summary of challenges, practices to address them, and research opportunities.

Intelligent and secure framework for critical infrastructure (CPS): Current trends, challenges, and future scope

Cyber–Physical Systems (CPS) are developed by the integration of computational algorithms and physical components and they exist as a result of technological advancement in embedded systems, distributed systems, and sophisticated networking technologies. Typically, these systems are intended to monitor and manipulate real-environment processes and objects. There had been advancements in CPS that affect various aspects of human lives and enable a wider range of applications and services. However, the interconnectivity between the cyber and physical world in CPS introduces new threats and security challenges and also increases the attack surface. The CPS is more prone to cyber-attacks than physical attacks because of the high accessibility of cyber components than physical ones. If we consider the last decade, it is no longer a myth to see industries relying on CPS being a victim of security attacks. In this paper, considering the applicability and dangers of CPS, we thus presented the key security aspects of CPS by reviewing published literature since 2018. We have examined the CPS requirements, challenges, security methods, security standards, threats, vulnerabilities, and past attacks. Moreover, we have considered the role of machine learning and deep learning in the enhancement of the security of CPS and reviewed the performance of existing works, and analyzed the challenges faced, and possible improvement techniques to enhance performance. We identified some key issues and challenges (such as CPS constraints, the performance of learning models, and security of learning models) in the adaption of learning-based methods for CPS security and accordingly proposed a security framework for CPS. Finally, several suggestions and recommendations are proposed considering the lessons learned from the comprehensive review.

Review on Security Analysis in Cyber Physical Systems

Cyber-Physical Systems (CPS) have seen a dramatic increase in research and real-world application in recent years. Many parts of our everyday lives have been affected, including electrical power systems, oil and gas delivery, transportation networks, medical equipment, home appliances, and a host of other areas. For example, many critical infrastructure and life support equipment are relying on these kinds of systems. As a result, they are required to be completely secure and resistant to all forms of assaults, which is almost unachievable for any real-world system. This paper focuses on security analysis in CPSs, whereby security in CPSs, security threats in CPSs, and security challenges in CPSs, have been discussed

Security and Privacy Challenges in the Deployment of Cyber-Physical Systems in Smart City Applications: State-of-Art Work

The concept “Smart City” is realized by incorporating advanced sensing and computational technologies in various processes, services, and infrastructure. Internet of Things (IoT) and Cyber-Physical Systems (CPS) are the key role players in the major development of smart city infrastructure. Further, the CPS stationing has improved the quality of various services like healthcare, transportation, environmental, etc., provided in a typical smart city ecosystem. But, the embodiment of CPS has also increased the surface area for cyber-attacks. In this paper, the various security and privacy issues at the different levels in the architecture of a smart city are discussed. The domain-centric security issues evolved with the deployment of CPS in transportation, healthcare, smart grids, and smart homes are also explored. Scopus publications for the years 2016–2020 are considered for the bibliometric analysis in security. It has been observed that a major number of security solutions have been proposed in the domain of smart homes during these years, whereas much scope is still there to address security and privacy challenges for CPS equipped smart grids. But over time, the security of smart grids is also becoming an area of interest for researchers. The article is concluded with the research gaps and future scope to cater secure smart city services.

Design Pedagogy: Pictographic Design Artefacts Perceived Artificial Intelligence Elements for Product Designers

This paper interprets a design pedagogy based on the Internet of Things (IoT) communication in the cyber-physical system challenges. This literature study discovers pictographic through artificial intelligence (AI). The product designers perceive the product form imaging beyond the engagement of design artefacts in the industrial design. The digital information sets are supplied through a design artefact evolution using heuristic evaluation. By the dual-method of designers’ human cognition, the design concept continuum develops arts and design education. The results identify an exact meaning of design pedagogy that the academicians will understand the specific content analysis type. Keywords: Artificial intelligence; industrial design; form imagery; internet of things eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v6iSI4%20(Special%20Issue%204).2901

An Adaptive Cuckoo Search-Based Optimization Model for Addressing Cyber-Physical Security Problems

One of the key challenges in cyber-physical systems (CPS) is the dynamic fitting of data sources under multivariate or mixture distribution models to determine abnormalities. Equations of the models have been statistically characterized as nonlinear and non-Gaussian ones, where data have high variations between normal and suspicious data distributions. To address nonlinear equations of these distributions, a cuckoo search algorithm is employed. In this paper, the cuckoo search algorithm is effectively improved with a novel strategy, known as a convergence speed strategy, to accelerate the convergence speed in the direction of the optimal solution for achieving better outcomes in a small number of iterations when solving systems of nonlinear equations. The proposed algorithm is named an improved cuckoo search algorithm (ICSA), which accelerates the convergence speed by improving the fitness values of function evaluations compared to the existing algorithms. To assess the efficacy of ICSA, 34 common nonlinear equations that fit the nature of cybersecurity models are adopted to show if ICSA can reach better outcomes with high convergence speed or not. ICSA has been compared with several well-known, well-established optimization algorithms, such as the slime mould optimizer, salp swarm, cuckoo search, marine predators, bat, and flower pollination algorithms. Experimental outcomes have revealed that ICSA is superior to the other in terms of the convergence speed and final accuracy, and this makes a promising alternative to the existing algorithm.

A Comparative Study of STPA-Extension and the UFoI-E Method for Safety and Security Co-analysis

Emerging challenges in cyber-physical systems (CPSs) have been encouraging the development of safety and security co-analysis methods. These methods aim at mitigating the new risks associated with the convergence of safety-related systemic flaws and security-related cyber-attacks that have led to major losses in CPSs. Although several studies have reviewed existing safety and security co-analysis methods, only a few empirical studies have attempted to compare their strengths and limitations to guide risk analysis in practice. This paper bridges the gap between two novel safety and security co-analysis methods and their practical implementations. Namely, this paper compares a novel extension of the System-Theoretic Process Analysis (STPA-Extension) and the Uncontrolled Flows of Information and Energy (UFoI-E) method through a common case study. In our case study, the CPS under analysis is a conceptual autonomous ship. We conducted our comparative study as two independent teams to guarantee that the implementation of one method did not influence the other method. Furthermore, we developed a comparative framework that evaluates the relative completeness and the effort required in each analysis. Finally, we propose a tailored combination of these methods, exploiting their unique strengths to achieve more complete and cost-effective risk analysis results.

Continuous experimentation and the cyber–physical systems challenge: An overview of the literature and the industrial perspective

Context:New software development patterns are emerging aiming at accelerating the process of delivering value. One is Continuous Experimentation, which allows to systematically deploy and run instrumented software variants during development phase in order to collect data from the field of application. While currently this practice is used on a daily basis on web-based systems, technical difficulties challenge its adoption in fields where computational resources are constrained, e.g., cyber–physical systems and the automotive industry. Objective:This paper aims at providing an overview of the engagement on the Continuous Experimentation practice in the context of cyber–physical systems. Method:A systematic literature review has been conducted to investigate the link between the practice and the field of application. Additionally, an industrial multiple case study is reported. Results:The study presents the current state-of-the-art regarding Continuous Experimentation in the field of cyber–physical systems. The current perspective of Continuous Experimentation in industry is also reported. Conclusions:The field has not reached maturity yet. More conceptual analyses are found than solution proposals and the state-of-practice is yet to be achieved. However it is expected that in time an increasing number of solutions will be proposed and validated.

Applications of model-driven engineering in cyber-physical systems: A systematic mapping study

Engineers face significant challenges in developing cyber-physical systems (CPS) due to their heterogeneous nature, i.e. the need for knowledge and skills from a wide range of academic and industrial disciplines, the integration of the artifacts of these disciplines and fields, and the difficulty of maintaining such heterogeneous artifacts should be taken into account. The development of CPS mostly needs a unified methodology that permits efficient raise of the abstraction level to overcome issues of heterogeneity induced by the multidisciplinary nature of the system. Model-driven engineering (MDE) is believed to be an alternative solution to overcome the challenges faced while developing CPS. This paper presents a systematic mapping study on using the MDE paradigm in CPS development and management. 140 research papers published during the period 2010–2018 are evaluated. The study mainly enables to find out the followed approaches when applying MDE for CPS, addressed CPS challenges, application domains and presented case studies. Results showed that the number of publications in this field is continuously increasing in recent years. Results also showed that metamodeling and model-based approaches are mostly adopted by the researchers affiliated to Europe, while DSL-based approach is adopted mostly by USA affiliated researchers. Only 45% of the studies consider a specific CPS application domain in which Smart Manufacturing is the most addressed domain followed by Critical Infrastructure, Health Care and Medicine. Moreover, the majority of the studies present case studies as the main evaluation method for the proposed MDE solutions. Conducting empirical evaluations is mostly missing. The results also revealed that various CPS challenges are addressed, and the most addressed ones are the complexity and interoperability aspects of CPS. Reporting on what previous researches have accomplished, as well as current research efforts and open challenges related to this field can guide researchers and developers in their further work on CPS design and implementation.

Literature review on Cyber Physical Systems Design

Cyber Physical Systems (CPS) are a disruptive technology currently in trend across many industries consisting of both computational and physical components working together to implement a process in real time, connecting, communicating and gathering all the information from defined sub-systems, creating large and complex systems. Currently there is no standardized design process for the development of a CPS, which is a challenge because these systems must be flexible and able to add more sub-systems at any point. Several research centers and universities around the world are creating learning factories, which are small-scale factories that will support knowledge development for Industry 4.0 topics and among these, CPS. This paper focuses in researching the current state of art, characteristics, design methodologies, applications, and challenges for CPS. The study also addresses the learning factories being developed and proposes further work.

Cognitive Modeling Approach for Dealing with Challenges in Cyber-Physical Systems

In this paper, inspired by our previous works, we propose an architecture for the design and realization of cyber-physical systems (CPS) that considers the spatio-temporal context of events, promotes anomaly detection, facilitates efficient human-computer interaction and is capable of discovering novel human and/or machine knowledge. We view deep neural networks as smart sensors and sensory data from the environment represents the semantic and episodic input to a consistency seeking component of the cyber-space. Starting from a knowledge base infused with a deterministic world assumption, this module can detect anomalies and correct estimation errors by combining the outputs of multiple sensors. We also exploit an episodic description of ongoing situations by integrating temporal segmentation with kernel and low-dimensional embedding based methods. We demonstrate parts of the architecture through illustrative examples on our self-collected driving dataset. Our framework can be related to cognitive science foundations and may facilitate reliable functioning of CPS through integrating traditional AI and deep learning methods with deterministic models and reasoning tools. We expect that such knowledge base and cognition driven approaches of joining deep neural networks will be adopted in complex CPS. This looks like a scalable, and beneficial match between human knowledge and the exploding deep learning technologies.

Dynamic Enhanced Field Division

Tracking moving objects is always a critical challenge in cyber-physical systems. Researchers have proposed many tracking algorithms. However, most of the proposed algorithms cannot be used for on-demand deployment because of the unavailable preset fingerprints (prior landmark or context information) in their assumption. Another issue is that those algorithms with models built in an interference-free environment cannot work in interference-rich environments. To address those issues, we propose a localizing and tracking algorithm called Enhanced Field Division (EFD), which dynamically divides the field into areas with unique signatures and tracks the target without any fingerprints. We also implemented a proof-of-concept localization platform to demonstrate the tracking accuracy and the algorithm performance in practical, interference-rich environments.

SD-CPS: software-defined cyber-physical systems. Taming the challenges of CPS with workflows at the edge

A cyber-physical system (CPS) is a smart mechanical environment, developed by an amalgamation of computation, networking, and physical dimensions. Each CPS consists of a network of devices, often limited in computing, storage, or bandwidth resources. Moreover, the frequent small-scale communications between the various counterparts of CPS require data and computation of CPS to be deployed close to each other, with the ability to support micro-executions. Due to these operational requirements, CPS faces several inherent challenges, uncommon to a traditional computational environment. In this paper, we describe software-defined cyber-physical systems (SD-CPS), a CPS framework built by extending and adapting the design principles of software-defined networking (SDN) into CPS. We realize the support for CPS operation as a workflow of microservices, possibly in continuous or cyclic execution. SD-CPS coordinates each CPS execution step, performed by a microservice, through an extended SDN controller architecture. By creating, placing, deploying, migrating, and managing the computation processes of CPS as service workflows at the edge, SD-CPS orchestrates the entire lifecycle of the CPS effectively and efficiently. SD-CPS thus addresses the general challenges of CPS, concerning modeling, development, performance, management, communication and coordination, scalability, and fault-tolerance, through its software-defined approach. Our evaluations highlight the efficiency of the SD-CPS framework and the scalability of its SDN controller to manage the complex CPS environments.

Privacy and security of big data in cyber physical systems using Weibull distribution-based intrusion detection

The volume of data collected from cyber physical systems (CPS) is huge, and we use big data techniques to manage and store the data. Big data in CPS is concerned with the massive heterogeneous data streams, which are acquired from autonomous sources and computed in distributed data storage system. In order to handle the size, complexity and rate of availability of data, it requires new techniques that can inspect and interpret useful knowledge from large streams of information, which impose challenges on the design and management of CPS in multiple aspects such as performance, energy efficiency, security, privacy, reliability, sustainability, fault tolerance, scalability and flexibility. This paper focuses on the security and privacy aspects in managing big data for CPS and reviews recent challenges in data privacy. We also present a protection framework for intrusion detection and analyze the performance parameters, reliability and failure rate in a malicious big data context.

Runtime management and quantitative evaluation of changing system goals in complex autonomous systems

A key challenge in cyber-physical systems (CPS) design is their highly dynamic nature including runtime changes of system goals. Additional safety regulations or changed priorities may apply, e.g. (temporarily) focusing on safety goals after some incident occurred. Goal-aware CPS continuously evaluate goal achievement and autonomously perform adaptations for re-achievement at runtime. For complex system goals capturing dependencies, priorities, and conflicts, efficient goal evaluation techniques are required. To enable a fine-grained balancing of the cost-benefit ratio of autonomous decisions at runtime, a qualitative evaluation of goals is not sufficient. We provide an algorithm that efficiently calculates the quantitative “distance” between a system state and the system goals. We organise various goal types, their parent-children-relationships, context-dependent importances, and dependency relations in a hierarchical goal model. Due to its modular structure, goals can easily be added, removed, and changed at runtime. We illustrate our approach with an exemplary autonomous air drone delivery system and discuss it based on illustrative example scenarios. We argue that our approach enables a) the design of complex context-dependent quantitative goal models for autonomous goal-aware systems, b) the measurement of the impact of autonomous decisions at runtime, and c) the efficient runtime management of changing system goals.

Mobile Cyber Physical Systems: Current Challenges and Future Networking Applications

Mobile cyber-physical systems (CPS) that take the advantages and extend the application domains of CPS have become increasingly popular in recent years. For example, mobile CPS could be a kind of foundational techniques to support the development of vehicular networking systems, thereby improving security and privacy of users in the dynamic environments of vehicular networks. In this paper, we first distinguish mobile CPS from traditional CPS. Then, we introduce their three emerging application areas, i.e., vehicular networking systems, healthcare systems, and mobile education . After that, we discuss four main research challenges of mobile CPS regarding security, energy consumption, mobile dynamic environment , and system stability . Also, we consider the corresponding techniques, which may address these challenges, and analyze the inter-relations among them. Finally, we outline the possible research directions and applications of mobile CPS in the future.