Cyber Security Of Control Systems Research Articles

An Accuracy-Maximization Approach for Claims Classifiers in Document Content Analytics for Cybersecurity

This paper presents our research approach and findings towards maximizing the accuracy of our classifier of feature claims for cybersecurity literature analytics, and introduces the resulting model ClaimsBERT. Its architecture, after extensive evaluations of different approaches, introduces a feature map concatenated with a Bidirectional Encoder Representation from Transformers (BERT) model. We discuss deployment of this new concept and the research insights that resulted in the selection of Convolution Neural Networks for its feature mapping aspects. We also present our results showing ClaimsBERT to outperform all other evaluated approaches. This new claims classifier represents an essential processing stage within our vetting framework aiming to improve the cybersecurity of industrial control systems (ICS). Furthermore, in order to maximize the accuracy of our new ClaimsBERT classifier, we propose an approach for optimal architecture selection and determination of optimized hyperparameters, in particular the best learning rate, number of convolutions, filter sizes, activation function, the number of dense layers, as well as the number of neurons and the drop-out rate for each layer. Fine-tuning these hyperparameters within our model led to an increase in classification accuracy from 76% obtained with BertForSequenceClassification’s original model to a 97% accuracy obtained with ClaimsBERT.

Measuring Stakeholder Alignment to Overcome Control System Cyber Vulnerability

Measuring Stakeholder Alignment to Overcome Control System Cyber Vulnerability

Learning Proposal for Cybersecurity for Industrial Control Systems Based on Problems and Established by a 4.0 Didactic Advanced-Manufacturing-Plant

Researches data indicate that the search for cybersecurity professionals to protect industrial control systems (ICS) in Brazil is increasing, mainly because of the rise in cyber-attacks directed at the industry. However, we observed a deficiency of professionals with the required competence in ICS cybersecurity, which involves technology-information fields (IT) and operational technology (OT). On the other hand, there is a lack of educational institutions with the right strategies for training professionals who master the technologies for ICS protection. This paper presents a strategy through procedures to address this lack by evaluating scenarios of practices for the development of competencies in ICS cybersecurity through the problem-based learning (PBL) methodology. The scenarios combine theory and practice involved in solving ICS cybersecurity problems, using PBL with the support of SENAI CIMATEC's 4.0 Advanced Manufacturing Plant (AMP).

Vertically Integrated Pathway for Infusing Engineering Technicians with Industrial Cybersecurity Competencies

This paper describes an effort to establish a vertically integrated pathway to identify and develop industrial control systems cybersecurity talent that extends from middle school to graduate degrees, leveraging the unique strengths of career and technical education. Educators and administrators seeking to ignite student interest in cybersecurity at a young age, and to provide a clear curriculum pathway to meet employer needs in the field of industrial cybersecurity may find this effort of use.

Changing the Paradigm of Control System Cybersecurity

Current cybersecurity protection relies on network monitoring. Changing the paradigm to monitor process sensors makes it practical to develop workable control system cybersecurity engineering solutions while simultaneously addressing reliability, safety, resilience, and productivity concerns.

Industrial Control System Cybersecurity Testbed with TSN Feature

Industrial Control System Cybersecurity Testbed with TSN Feature

Quantum Computing and Resilient Design Perspectives for Cybersecurity of Feedback Systems

Cybersecurity of control systems is an important issue in next-generation manufacturing that can impact both operational objectives (safety and performance) as well as process designs (via hazard analysis). Cyberattacks differ from faults in that they can be coordinated efforts to exploit system vulnerabilities to create otherwise unlikely hazard scenarios. Because coordination and targeted process manipulation can be characteristics of attacks, some of the tactics previously analyzed in our group from a control system cybersecurity perspective have incorporated randomness to attempt to thwart attacks. The underlying assumption for the generation of this randomness has been that it can be achieved on a classical computer; however, quantum computers can also create random behavior in the results of computations. This work explores how errors in quantum hardware that can create non-deterministic outputs from quantum computers interact with control system cybersecurity. These studies serve as a reminder of the need to incorporate cybersecurity considerations at the process design stage.

A note on diagnosis and performance degradation detection in automatic control systems towards functional safety and cyber security

This note addresses diagnosis and performance degradation detection issues from an integrated viewpoint of functionality maintenance and cyber security of automatic control systems. It calls for more research attention on three aspects: (i) application of control and detection unified framework to enhancing the diagnosis capability of feedback control systems, (ii) projection-based fault detection, and complementary and explainable applications of projection- and machine learning-based techniques, and (iii) system performance degradation detection that is of elemental importance for today’s automatic control systems. Some ideas and conceptual schemes are presented and illustrated by means of examples, serving as convincing arguments for research efforts in these aspects. They would contribute to the future development of capable diagnosis systems for functionality safe and cyber secure automatic control systems.

Secure Teleoperation Control Using Somewhat Homomorphic Encryption

The goal of this research is to establish control theoretic methods to enhance cyber security of networked motion control systems by utilizing somewhat homomorphic encryption. The proposed approach will encrypt the entire motion control schemes including: sensor signals, model parameters, feedback gains, and performs computation in the ciphertext space to generate motion commands to servo systems without a security hole. The paper will discuss implementation of encrypted bilateral teleoperation control schemes with nonlinear friction compensation. The paper will present (1) encrypted teleoperation control realization with somewhat homomorphic encryption and (2) simulation results.

Remote training in cybersecurity for industrial control systems

Cybersecurity is a key subject for digital transformation where institutional, industrial and educational sectors should be involved in a coordinated way. Currently, there is a lack of workforce with essential competences to apply secure solutions in an industrial environment. For that reason, in order to address this increasing demand, universities promote industrial cybersecurity courses and related programs. But training of future cybersecurity professionals in the industrial sector requires appropriate frameworks that facilitate teaching students a range of evolving technologies. In this work, a platform for remote training in cybersecurity is proposed using cabinets that include specific elements for automation and control as well as additional resources for administration and communication tasks. The platform allowed the development of two cybersecurity courses whose students were asked for feedback about the structure of the laboratory, its operation and also the learning process. The results show a wide acceptance of the platform used in the course and an improvement of students’ motivation in the subject.

Flood Type DoS Attack Mitigation Technology for Cybersecurity in Industrial Control Systems

Flood Type DoS Attack Mitigation Technology for Cybersecurity in Industrial Control Systems

Explainable Anomaly Detection for Industrial Control System Cybersecurity

Industrial Control Systems (ICSs) are becoming more and more important in managing the operation of many important systems in smart manufacturing, such as power stations, water supply systems, and manufacturing sites. While massive digital data can be a driving force for system performance, data security has raised serious concerns. Anomaly detection, therefore, is essential for preventing network security intrusions and system attacks. Many AI-based anomaly detection methods have been proposed and achieved high detection performance, however, are still a ”black box” that is hard to be interpreted. In this study, we suggest using Explainable Artificial Intelligence to enhance the perspective and reliable results of an LSTM-based Autoencoder-OCSVM learning model for anomaly detection in ICS. We demonstrate the performance of our proposed method based on a well-known SCADA dataset.

Analyzing the Impact of Cybersecurity on Monitoring and Control Systems in the Energy Sector

Monitoring and control systems in the energy sector are specialized information structures that are not governed by the same information technology standards as the rest of the world’s information systems. Such industrial control systems are also used to handle important infrastructures, including smart grids, oil and gas facilities, nuclear power plants, water management systems, and so on. Industry equipment is handled by systems connected to the internet, either via wireless or cable connectivity, in the present digital age. Further, the system must work without fail, with the system’s availability rate being of paramount importance. Furthermore, to certify that the system is not subject to a cyber-attack, the entire system must be safeguarded against cyber security vulnerabilities, threats, and hazards. In addition, the article looks at and evaluates cyber security evaluations for industrial control systems, as well as their possible impact on the accessibility of industrial control system operations in the energy sector. This research work discovers that the hesitant fuzzy-based method of the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is an operational procedure for estimating industrial control system cyber security assessments by understanding the numerous characteristics and their impacts on cyber security industrial control systems. The author evaluated the outputs of six distinct projects to determine the quality of the outcomes and their sensitivity. According to the results of the robustness analysis, alternative 1 shows the utmost effective cybersecurity project for the industrial control system. This research work will be a conclusive reference for highly secure and managed monitoring and control systems.

Operational Technology on Construction Sites: A Review from the Cybersecurity Perspective

The digital transformation in the construction industry affects how information is exchanged and disrupts the way construction sites operate. The levels of operational technology (OT) to control and monitor site activities by utilizing robotic, autonomous, and remotely controlled machines raise cybersecurity concerns. As construction sites are places where humans and machines work together, the potential safety outcomes of cybersecurity vulnerabilities are magnified. This study’s motivation was to understand the current state of the art and identify gaps to suggest future directions regarding OT in construction from the cybersecurity perspective. To achieve that, a bibliometric analysis was conducted. The analysis utilized the Scopus database to retrieve related publications and VOSviewer version 1.6.15 software to visualize bibliometric networks. Main research themes were identified, and each theme was reviewed from a cybersecurity perspective. The limitations of the analysis include the lack of industry-based categorization, the domination of publications focusing on the cybersecurity of industrial control systems (ICSs), and the set of keyword combinations used for the literature search that could be expanded to cover a broader range of research topics. The findings reveal the lack of focus on the construction phase in the construction cybersecurity research. Moreover, cybersecurity aspects are absent in the construction automation studies, and there is a need for bespoke threat modeling and intrusion detection systems for all the phases of construction projects. Suggestions for further research on the potential threats against the construction phase are provided. Future directions include possible adaptations of the available cybersecurity frameworks considering the utilization of OT on construction sites and investigating the methods to evaluate security levels on construction sites and countermeasures against cyberattacks.

Analysis and Application of intelligent Power Control System Cyber Security Situation Awareness Based on Wavelet Neural Network

In recent years, international industrial control network security incidents have occurred frequently. As a core component of the industrial control field, intelligent power control systems are increasingly threatened by external network attacks. Based on the current research status of power industrial control network security, closely combining the development of active monitoring and defense technology in the public network field and the problems encountered by network security operators in actual work, this paper uses data mining methods to study the power control system network security situation awareness technology. Combing operational data collection and integrated processing, situation index screening and extraction, we use wavelet neural network analysis method to train the sampled data set, and finally calculate the true value of the network security status through deep intelligent learning. Finally, we conclude that the artificial intelligence algorithm based on wavelet neural network can be used for power control system network security situation awareness. In actual work, it can predict the situation value for a period of time in the future and assist network security personnel in judgment and decision-making.

Control Systems Cyber Security Reference Architecture (RA) for Critical Infrastructure: Healthcare and Hospital Vertical Example

A reference architecture (RA) provides a common frame of reference with a common vocabulary, reusable designs, and principles that may be applied to future architectures. It can promote re‐use of best practices, improve interoperability, and improve awareness of a system under development of the same mindset. The next version of the Department of Defense (DoD) Chief Information Officer (CIO) Cyber Security Reference Architecture (CSRA) will include an appendix for control systems. It provides a frame of reference for cybersecurity implementations based on generalizations of common principles that can provide a starting point for an organization's architecture effort, inform decision‐making, suggest governance, and help define future policy decisions for control systems. The appendix is based on the outcome of the MOSIACS Joint Capability Technology Demonstration (JCTD), which provides the initial cyber defensive capability framework for integrations of Commercial‐Off‐The‐Shelf (COTS) and Government‐Off‐The‐Shelf (GOTS) components to form a control system cyber defensive solution. The MOSAICS capability was successfully demonstrated in the energy sector critical infrastructure vertical on a power system in August 2021. Its applicability embodied delivery methods for technologies in other essential infrastructure sectors, repeatable playbooks for automated Courses of Action (COA), best practices, and templates for cyber security requirements for control systems. The advantages of the RA are to enable better decision‐making and policy‐making support about cybersecurity for control systems. This paper demonstrates the RA used in the Healthcare and Public Health sector's critical infrastructure vertical to evaluate concepts such as Zero Trust (ZT) and Defense‐in‐Depth (DiD) architecture principles related to policymaking.

Risk Measurement and Cyber security in Industrial Control Systems

In this new era of expansion in the cyber space, it is not just the IT domain that is vulnerable to cyber-attacks but also the Industrial Control Systems (ICS). ICS is vital in the functioning of almost all the industries either directly or indirectly. As we progress in the direction of Industry 4.0, the challenges with respect to the security of these systems and the data associated with it needs to be addressed. Vulnerability of these systems to various attacks in the past, increases the need for a secured infrastructure. In this paper, the security of ICS along with the importance of software patching and the calculation of the risk associated with the negligence in the process is discussed.

Мониторинг кибербезопасности сложных информационных и управляющих систем критической инфраструктуры

Approaches to the complex solution of problems of monitoring cybersecurity of complex information and control systems are considered. A formalized description and interrelationship of the processes of ensuring cybersecurity and monitoring of cybersecurity are presented. The results of research on the implementation of monitoring processes for cybersecurity of complex information and control systems are presented.

Situation awareness framework for industrial control system based on cyber kill chain

Information and cyber security of Industrial Control Systems (ICS) has gained considerable importance. Situation Awareness (SA) is an exciting mechanism to achieve the perception, comprehension and projection of the ICS information security status. Based on the Purdue Enterprise Reference Architecture (PERA), a situation awareness framework for ICS is presented considering the ICS cyber kill chain. The proposed framework consists of IT SA Centre, OT SA Centre, and Comprehensive SA Centre. Comprehensive SA Centre is responsible for creating and maintaining an integrated and high level of security visibility into the whole environments. The introduced framework can be used to guide the development of the situation awareness infrastructure in organization with industrial control systems.

Control system report finds poor security

KPMG and the Control System Cyber Security Association International – aka (CS)2AI – have released the first of what will become an annual series of reports looking at control system (CS) and operational technology (OT) security.