Cyber Components Research Articles

Petri Nets-Based Modeling Solution for Cyber–Physical Product Control Considering Scheduling, Deployment, and Data-Driven Monitoring

For a complex electromechanical product that is a cyber–physical system (CPS), its dynamic behaviors are embodied in the closed-loop control between the logic process in its cyber component and actual actuators/sensors in its physical component, and thus, a well-defined model of the control is important to create a digital twin that acts as much like the real machine as possible. This article proposes a Petri nets (PNs)-based modeling solution that employs hybrid PNs (HPNs) for physics and system of sequential systems with shared resources (S4R) nets for logic in building a hierarchical control model. We also present PNs technologies for implementing a smooth transition and bidirectional mapping from the virtual prototype to the real machine. These technologies involve a PNs integration of a reinforcement learning (RL) method for generating a workflow scheduling agent in design, an extension of PNs definitions that is compatible with the microcontroller for easy deployment in manufacturing, and an architecture of PNs execution recording for data-driven monitoring in service. A software kit is provided for the solution that includes an integrated development environment of PNs, tools for quickly building a virtual prototype, and a monitor server for remote data-driven monitoring. This solution is successfully applied in the development of a typical cyber–physical product case, namely, the chemiluminescence immunoassay (CLIA) analyzer.

The Exigency for Resilient and Cyber-Secure Critical Infrastructure in the Caribbean

Critical Infrastructures (CIs) are essential assets used to maintain vital societal functions, for example utilities such as power, water, gas, and telecommunication networks. CIs comprise two main parts, namely a: Cyber component and a Physical component, which allow them to operate. Therefore, the occurrence of faults or attacks in either domain can result in the disruption of services, causing negative impacts beyond the system itself. The purpose of this article is to raise awareness within Trinidad and Tobago and, by extension, the Caribbean on the importance of maintaining resilient and cyber secure CIs for the purpose of critical infrastructure protection (CIP) given the current situation. A review of past incidents from 2012 - 2022 taken place both regionally and internationally is discussed, with major emphasis on those occurring in the Caribbean region. These incidents have been presented from the perspective of faults and cyber-attacks affecting CIs resulting in the disruption of services. In responding to frequently occurring scenarios, recommendations on the way forward have been proposed. Keywords: Critical Infrastructures (CIs), Critical Infrastructure Protection (CIP), Resilient Control, Cyber-attacks, Fault Tolerant Control

An integrated outlook of Cyber–Physical Systems for Industry 4.0: Topical practices, architecture, and applications

Industry 4.0 requires a strong understanding of Cyber-Physical systems (CPS). An Industry 4.0-enabled manufacturing environment that offers real-time data gathering, transparency and analysis across all parts of a manufacturing process is known as cyber–physical systems, also known as cyber manufacturing. Data analytics enables executives to make data-driven choices and boost productivity, while automation speeds up manufacturing and decreases machine downtime. The main objective of deploying Industry 4.0 solutions is to enable manufacturing organisations to increase collaboration by making the correct information accessible to the right people in real time. The aim of encouraging optimal decision-making at the appropriate moment is to improve efficiency and production further. The critical terms in Industry 4.0, such as the CPS, Internet of Things (IoT), and Digital Twin, are widely used interchangeably in conversations about smart manufacturing. These are essential to Industry 4.0 and smart manufacturing because they give users access to real-time operating data of the equipment they represent. Cyber components and physical components make up the two elements of CPS. The main aim of this paper is to brief CPS and its need for Industry 4.0. Embedded Processes and Smart 5C diagrammatically elaborate architecture of CPS for Industry 4.0. Finally, the paper identifies and discusses significant applications of CPS in Industry 4.0. For this paper, we identified and then studied relevant literature on CPS for establishing an Industry 4.0 environment. CPS is integrated into several items, including vehicles and other equipment, to carry out particular functions. CPS can be utilised in any industry, including engineering, manufacturing, transportation, and even health care, because they are all easy to use. CPS network collaborative systems are built for communication. Furthermore, cutting-edge network technologies like cloud solutions are used by CPS. • Industry 4.0 requires a strong understanding of Cyber-Physical systems (CPS). • Industry 4.0 enable manufacturing increase collaboration through CPS. • This paper brief about CPS and its need for Industry 4.0. • Embedded Processes and Smart 5C Architecture of CPS for Industry 4.0 are elaborated. • Finally, paper identifies and discusses significant applications of CPS for Industry 4.0.

Population processes in cyber system variability.

Variability is inherent to cyber systems. Here, we introduce ideas from stochastic population biology to describe the properties of two broad kinds of cyber systems. First, we assume that each of N0 components can be in only one of two states: functional or nonfunctional. We model this situation as a Markov process that describes the transitions between functional and nonfunctional states. We derive an equation for the probability that an individual cyber component is functional and use stochastic simulation to develop intuition about the dynamics of individual cyber components. We introduce a metric of performance of the system of N0 components that depends on the numbers of functional and nonfunctional components. We numerically solve the forward Kolmogorov (or Fokker-Planck) equation for the number of functional components at time t, given the initial number of functional components. We derive a Gaussian approximation for the solution of the forward equation so that the properties of the system with many components can be determined from the transition probabilities of an individual component, allowing scaling to very large systems. Second, we consider the situation in which the operating system (OS) of cyber components is updated in time. We motivate the question of OS in use as a function of the most recent OS release with data from a network of desktop computers. We begin the analysis by specifying a temporal schedule of OS updates and the probability of transitioning from the current OS to a more recent one. We use a stochastic simulation to capture the pattern of the motivating data, and derive the forward equation for the OS of an individual computer at any time. We then include compromise of OSs to compute that a cyber component has an unexploited OS at any time. We conclude that an interdisciplinary approach to the variability of cyber systems can shed new light on the properties of those systems and offers new and exciting ways to understand them.

Guest Editorial: Learning, optimisation and control of cyber‐physical systems

Guest Editorial: Learning, optimisation and control of cyber‐physical systems

Automation industry in cyber physical systems based on 4G IoT networks for operation controlling and monitoring management

Cyber-Physical System (CPS) is an emerging technique that focuses on the integration of computation applications as a network of communicating physical and cyber components which controls real time physical substructures of the industrial automation. Since implementation, operation and design of CPS and management of automation substructures are plays major significance in the various industrial applications. This study presents a Deep learning (DL) based intrusion controlling and monitoring management system (DL-ICMMS) for CPS in the automation industry for the detection of the occurrence of intrusions. To transform the input data in a compatible manner, data normalization is carried out and the Adam optimizer is applied to handle hyperparameter values of Restricted Boltzmann Machine (RBM) method. Experimental results analysis stated that the DL-ICMMS method increased accuy of 98.80% whereas the Multilayer Perceptron (MLP), K Nearest Neighbor (KNN), Deep Belief Network (DBN), Convolutional Neural Network (CNN), and Long short-term memory (LSTM) approaches have shown reduced accuy of 93.10%, 93.62%, 91.60%, 90.88%, and 91.75%, correspondingly.

Guest Editorial Special Issue on Security, Privacy, and Trustworthiness in Intelligent Cyber–Physical Systems and Internet of Things

Recent advances in computation, communication, and control technologies have revolutionized the way that humans, smart things, and intelligent systems interact and exchange information. Intelligent cyber–physical systems (ICPSs), characterized by the deep complex intertwining process among cyber components for computation and control with intelligent technologies and the dynamic physical components, will fuel this revolution. Examples of ICPS include intelligent automotive and transportation systems, intelligent avionics systems, smart home, smart building, smart community, smart grid, smart healthcare systems, intelligent wearable systems, intelligent energy systems, robotic systems, etc. Bringing machine/deep-learning-based intelligence techniques into CPSs can improve the performance in many aspects. However, this also imposes new security, privacy, and trust challenges, which highlights the need to develop novel methodologies to tackle these challenges. In this special issue, we will publish the following articles.

Industrial Control Systems Security via Runtime Enforcement

With the advent of Industry 4.0 , industrial facilities and critical infrastructures are transforming into an ecosystem of heterogeneous physical and cyber components, such as programmable logic controllers , increasingly interconnected and therefore exposed to cyber-physical attacks , i.e., security breaches in cyberspace that may adversely affect the physical processes underlying industrial control systems . In this article, we propose a formal approach based on runtime enforcement to ensure specification compliance in networks of controllers, possibly compromised by colluding malware that may locally tamper with actuator commands, sensor readings, and inter-controller communications. Our approach relies on an ad-hoc sub-class of Ligatti et al.’s edit automata to enforce controllers represented in Hennessy and Regan’s Timed Process Language . We define a synthesis algorithm that, given an alphabet 𝒫 of observable actions and a timed correctness property e , returns a monitor that enforces the property e during the execution of any (potentially corrupted) controller with alphabet 𝒫, and complying with the property e . Our monitors do mitigation by correcting and suppressing incorrect actions of corrupted controllers and by generating actions in full autonomy when the controller under scrutiny is not able to do so in a correct manner. Besides classical requirements, such as transparency and soundness , the proposed enforcement enjoys deadlock- and diverge-freedom of monitored controllers, together with scalability when dealing with networks of controllers. Finally, we test the proposed enforcement mechanism on a non-trivial case study, taken from the context of industrial water treatment systems, in which the controllers are injected with different malware with different malicious goals.

Plan B: Design Methodology for Cyber-Physical Systems Robust to Timing Failures

Many Cyber-Physical Systems (CPS) have timing constraints that must be met by the cyber components (software and the network) to ensure safety. It is a tedious job to check if a CPS meets its timing requirement especially when it is distributed and the software and/or the underlying computing platforms are complex. Furthermore, the system design is brittle since a timing failure can still happen (e.g., network failure, soft error bit flip). In this article, we propose a new design methodology calledPlan Bwhere timing constraints of the CPS are monitored at runtime, and a proper backup routine is executed when a timing failure happens to ensure safety. We provide a model on how to express the desired timing behavior using a set of timing constructs in a C/C++ code and how to efficiently monitor them at the runtime. We showcase the effectiveness of our approach by conducting experiments on three case studies: (1) the full software stack for autonomous driving (Apollo), (2) a multi-agent system with 1/10th-scale model robots, and (3) a quadrotor for search and rescue application. We show that the system remains safe and stable even when intentional faults are injected to cause a timing failure. We also demonstrate that the system can achieve graceful degradation when a less extreme timing failure happens.

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.

A practical physical watermarking approach to detect replay attacks in a CPS

Cyber Physical Systems (CPSs) are considered as an integration of computing, networking, and physical processes. In such systems physical processes are monitored and controlled by the combination of computation, communication, and control technologies. Examples of CPSs include process control systems, medical devices, robots, and critical infrastructures such as water treatment plants, water distribution systems, and power grid. Often, these systems are vulnerable to attacks as the cyber components such as Supervisory Control and Data Acquisition (SCADA) workstations, Human Machine Interface (HMI), and Programmable Logic Controllers (PLCs) are potential targets for attackers. Replay attacks are easy to perform on such systems and can potentially lead to significant damages to the system. Therefore, timely detection of replay attacks is important to mitigate the attack consequences. In this work, we propose a practical watermarking technique to detect the attacks. Experiments are performed on a real WAter DIstribution system (WADI) to explore how to tackle the replay attacks using watermarking signal.

Safety Impact Analysis Considering Physical Failures and Cyber-Attacks for Mechanically Pumped Loop Systems (MPLs).

As complex systems composed of physical and cyber components, mechanically pumped loop systems (MPLs) are vulnerable to both passive threats (e.g., physical failures) and active threats such as cyber-attacks launched on the network control systems. The impact of the aforementioned two threats on MPL operations is yet unknown, and there is no practical way to evaluate their severity. To assess the severity of the impact of physical failures and cyber-attacks on MPLs, a safety impact analysis framework based on Elman Neural Network (ENN) observers and the Gaussian Mixture Model (GMM) algorithm is suggested. The framework discusses three common attack and failure modes: sensor hard failure that occurs suddenly, sensor soft failure that occurs gradually over time, and denial-of-service (DoS) attacks that prevent communication between the controller and valve. Both sensor failures and DoS attacks render the system unsafe, according to simulation data. In comparison to DoS attacks, however, sensor failures, particularly soft failures, inflict the greatest harm to the MPLs. Furthermore, sensors engaged in global control, rather than those involved in local control, need additional protection.

Теоретико-ігрові та оптимізаційні моделі і методи підвищення безпеки кіберінфраструктур

Критична інфраструктура взаємозалежних сучасних секторів все більше покладається на кіберсистеми та кіберінфраструктури, які характеризуються зростанням ризиків їх кіберкомпонентів, у тому числі кіберфізичних підсистем. Тому кібербезпека є важливою для захисту критичної інфраструктури. Пошук економічно ефективних шляхів підвищення або підвищення безпеки кіберінфраструктури базується на оптимізаційних моделях і методах стабільності, безпеки та надійності кіберінфраструктури. Ці моделі та методи мають різні сфери застосування та різні напрямки, не обов’язково орієнтовані на стійкість кіберінфраструктури. Зростання ролі інформаційно-комунікаційних технологій вплинуло на концепцію безпеки та характер війни. Багато критичних інфраструктур (аеропорти, лікарні, нафтопроводи) стали потенційно вразливими для організованих кібератак. Сьогодні здійснення головної державної функції оборони і безпеки значною мірою залежить від успішного застосування інформаційно-комунікаційних технологій як сучасних конкурентоспроможних (кінцевих і проміжних) продуктів подвійного призначення, які використовують різні особи з різними цілями. Теорію ігор усе більше застосовують для оцінювання стратегічних взаємодій між нападниками й оборонцями у кіберпросторі. Для дослідження безпеки кіберпростору поєднуються підходи теорії ігор і моделювання. У кіберпросторі арсенал зброї будується шляхом знаходження більшої кількості уразливіших місць у захисті цілі. Вразливість — це слабкість у процедурах безпеки системи, проєкті системи чи його реалізації, а також в організації внутрішнього контролю, якими може скористатися джерело загрози. Динамічний характер вразливостей означає, що вони постійно змінюються з часом. Виявлення вразливості оборонцем знижує ефективність кіберзброї нападника, яка користується даною вразливістю, і підвищує захист цілі. Теорія ігор застосовувалася для вирішення багатьох проблем, включаючи розподіл ресурсів, безпеку мережі, кооперацію осіб. У кіберпросторі часто зустрічається гра розміщення, де нападник і оборонець приймають рішення, куди розподіляти свої відповідні ресурси. Ресурсами оборонця можуть бути інфраструктура безпеки (брандмауери), фінанси, підготовка кадрів. Наприклад, адміністратор мережі може шукати таке розміщення ресурсів, яке мінімізує ризики кібератак (нападів) і водночас витрати захисту від кібератак. Нападник має обмежені ресурси і зазнає ризику бути відстеженим і покараним. Проблему розподілу ресурсів у кіберпросторі можна сформулювати як теоретико-ігрову задачу з урахуванням поняття загального знання і проблеми невизначеної спостережуваності.

Design of AC state estimation based cyber-physical attack for disrupting electricity market operation under limited sensor information

The deregulated electricity market operation in smart grid has resulted in a conducive scenario for both the utility and consumer. However, the deep integration of cyber components in the physical infrastructure has increased the vulnerability to attacks by intruders. As compared to an isolated cyber or physical attack, the coordinated attack involving both the physical and cyber layer has a wider impact on the smart grid operation. This paper proposes an AC state estimation (AC-SE) based coordinated cyber-physical attack for disrupting the market operation by manipulating the nodal price. Knowledge of the system configuration and real-time sensor information eases the task of launching an attack. However, the availability of such knowledge is somewhat unrealistic due to accessibility and budget constraints. In this regard, the proposed attack design considers the realistic scenario of incomplete information regarding network topology and sensor data. The first stage of the attack involves identifying the most vulnerable branch that causes maximum deviation in the nodal price allocation between pre-attack and post-attack scenarios. In the second stage, a cyber-attack is synthesized to hide the impact of a physical attack. The effectiveness of the scheme has been validated on benchmark IEEE 14,39, and 118 bus power systems.

Towards analyzing the impact of intrusion prevention and response on cyber-physical system availability: A case study of NPP

The idea of industry 4.0 is quite pertinent for CPS. The integration of cyber components enhances a physical system’s capabilities by incorporating intelligence into objects and services. On the other hand, these systems are more vulnerable to cyber-attacks than traditional hard-wired electro-mechanical systems and infrastructure as they are accessible through the Internet. Most of such systems are safety–critical, where successful attacks may result in catastrophic situations by disturbing a critical system’s functionalities. To disrupt the physical process, the attacker should have a deep understanding of operational and control parameters and failure conditions of system components. The attacker first intrudes into the system and subsequently abuses the process parameters to disrupt the physical process. Consideration of these issues is important to evaluate the security of CPS. Hence, this work presents a Generalized Stochastic Petri Net (GSPN) based approach to analyze the effect of integrating the preventive and reactive measures against cyber attacks. By analyzing the model, system security is quantitatively estimated in terms of security metrics such as mean-time-to disrupt and system availability. We validate the combined effect of preventive and responsive measures on a case study of Nuclear power plant (NPP), which is one of the primary sources of electric power generation.

Precision timing and communication networking experiments in a real-time power grid hardware-in-the-loop laboratory

The growing wave of digitization in power grids is bringing increased reliance on information and communication technologies (ICT) for the operation of the grid. Such cyber–physical power systems (CPPS) involve the interaction of the physics of the power grid with the performance of other engineered systems, such as communications and time-synchronization. To understand the interplay of such interactions, experimentation is required. However, there are very limited opportunities to perform experiments on actual CPPS systems, due to safety and security concerns. Nevertheless, the demand for more functionalities on cyber components will continue to rise, and thus, other means to understand CPPS behavior for design, implementation and testing are needed. To address this gap, a real-time simulator-based power system laboratory was implemented with the objective of facilitating experiments involving precision timing and communication networking systems which are coupled with power grid models running in real-time. These are integrated in three layers: (a) Precise Timing Layer, (b) Communication/Network Layer, and (c) Electrical Component Layer. This paper reports on detailed experiments performed on the precision timing and communication layers of the laboratory. It shows how to couple the different layers together, and how to conduct experiments to tamper with both the precision timing and communication layers, along with their interactions with the simulated grid. Finally, the paper shows how to validate the Quality of Service (QoS) rules implemented in virtual local area networks (VLANs) in the laboratory environment when using different power system communication protocols.

Distributed Observer-based Cyber-security Control of Complex Dynamical Networks

A large number of interconnected nodes in which each node is a nonlinear dynamic system is a complex dynamic system. Complex cyber physical system refers to a new generation of complex systems which depend on close interactions between their physical components and cyber components. Many modern critical infrastructures as complex cyberphysical systems can be appropriately modelled. Distributed network is used in computer distribution. The distributed network infrastructure in the computer application, software and its data is distributed across many computers. The objective of the distributed network to share the resource, usually with a specific or comparable objective. With a lower transmission implication and computation costs in CPS, the proposed distributed cyber-physical algorithms will converge fast and thus increase the reliability. The results of the simulation verify the feasibility of the solution proposed.

Multi-State Reliability Assessment Model of Base-Load Cyber-Physical Energy Systems (CPES) during Flexible Operation Considering the Aging of Cyber Components

Cyber-Physical Energy Systems (CPESs) are energy systems which rely on cyber components for energy production, transmission and distribution control, and other functions. With the penetration of Renewable Energy Sources (RESs), CPESs are required to provide flexible operation (e.g., load-following, frequency regulation) to respond to any sudden imbalance of the power grid, due to the variability in power generation by RESs. This raises concerns on the reliability of CPESs traditionally used as base-load facilities, such as Nuclear Power Plants (NPPs), which were not designed for flexible operation, and more so, since traditionally only hardware components aging and stochastic failures have been considered for the reliability assessment, whereas the contribution of the degradation and aging of the cyber components of CPSs has been neglected. In this paper, we propose a multi-state model that integrates the hardware components stochastic failures with the aging of cyber components, and quantify the unreliability of CPES in load-following operations under normal/emergency conditions. To show the application of the reliability assessment model, we consider the case of the Control Rod System (CRS) of a NPP typically used for a base-load energy supply.

Model based security verification of Cyber-Physical System based on Petrinet: A case study of Nuclear power plant

A variety of modern Cyber-Physical Systems (CPSs) are distributed and asynchronous systems that are becoming the backbone for smart infrastructures and systems such as smart grids, power plants, medical appliances, social robots etc. The weaving of cyber components with the physical system improves resource utilization and system reliability. However, it makes the CPSs significantly vulnerable to several cyber threats by increasing the attack surfaces. In safety-critical cyber-physical systems, the primary focus is on safety assurance. Any mistake or ignorance in security analysis may greatly amplify the losses in the presence of cyber threats. Such security failure may result in severe damages that may range from affecting critical infrastructures up to even loss of human lives. Thus, an early-staged security modeling of these systems is a prominent issue and requires a systematic approach for modeling a secure design as well as performance evaluation of alternative designs for the same. An in-depth security analysis involves the identification of a standard set of evaluation metrics. The proposed work provides the design-time methodology to map and analyze system security qualitatively and quantitatively using Stochastic Petri nets and their fundamental properties. The effectiveness of the proposed methodology is evaluated using a Nuclear power plant (NPP) case study.

An ethical decision-making framework with serious gaming: a smart water case study on flooding

AbstractSensors and control technologies are being deployed at unprecedented levels in both urban and rural water environments. Because sensor networks and control allow for higher-resolution monitoring and decision making in both time and space, greater discretization of control will allow for an unprecedented precision of impacts, both positive and negative. Likewise, humans will continue to cede direct decision-making powers to decision-support technologies, e.g. data algorithms. Systems will have ever-greater potential to effect human lives, and yet, humans will be distanced from decisions. Combined these trends challenge water resources management decision-support tools to incorporate the concepts of ethical and normative expectations. Toward this aim, we propose the Water Ethics Web Engine (WE)2, an integrated and generalized web framework to incorporate voting-based ethical and normative preferences into water resources decision support. We demonstrate this framework with a ‘proof-of-concept’ use case where decision models are learned and deployed to respond to flooding scenarios. Findings indicate that the framework can capture group ‘wisdom’ within learned models to use in decision making. The methodology and ‘proof-of-concept’ system presented here are a step toward building a framework to engage people with algorithmic decision making in cases where ethical preferences are considered. We share our framework and its cyber components openly with the research community.