Protection Of Critical Assets Research Articles

The resilience of critical information infrastructure topology in the cyberspace

Modern trends in the decentralization and branching of systems that process, store, and transmit information enhance system resilience. Increasingly, technological systems and operational technologies rely on electronic communications from third-party operators and cyberspace. However, these trends introduce new cybersecurity challenges and contradictions. This article presents risk-informed approaches to designing and modernizing the topology of critical information infrastructure (CII). Such approaches involve making decisions and implementing security measures based on a thorough assessment of organizational risks. By evaluating the likelihood and impact of threats, vulnerabilities, and potential consequences, resources are prioritized to achieve a balance between security, functionality, and cost-effectiveness. The recommendations focus on practices for assessing cybersecurity risks, particularly those arising from cyberattacks targeting external (cyberspace) connections of CII. They also emphasize enhancing the protection of critical information assets from such threats. Unlike general cybersecurity measures, these recommendations specifically address risks associated with CII’s cyberspace topology, providing additional or supplementary measures to existing procedures within the information security lifecycle.

Fortifying the Connection: Cybersecurity Tactics for WSN-Driven Smart Manufacturing in the Era of Industry 5.0

Wireless Sensor Network (WSN)-based manufacturing facilities in the context of the Fourth Industrial Revolution (Industry 5.0) represent advanced Cyber-Physical Production Systems (CPPSs), wherein seamless networking of people, objects, and machines is achieved across the entire supply chain. A significant advantage of such digitization is the facilitation of personalized and agile manufacturing processes. However, this interconnectedness introduces a spectrum of novel threat vectors, enabling sophisticated Distributed Denial-of-Service (DDoS) attacks. One critical vulnerability lies in the Internet of Things (IoT) sensor nodes. These IoT devices, now extensively utilized for sensing, data acquisition, analysis, and communication within manufacturing environments, have concomitantly escalated the risk of cyber threats. To counteract these threats, advanced intrusion detection systems leveraging deep learning algorithms have emerged as scalable and intelligent solutions for safeguarding industrial IoT and WSN infrastructures. This paper introduces a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model tailored for cybersecurity attack detection in industrial IoT environments, specifically within WSN-based smart manufacturing contexts. The proposed CNN-LSTM model exhibits superior efficacy in identifying DDoS attacks within Industry 5.0 CPS environments, surpassing conventional Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) models in terms of accuracy, precision, recall, and F1-score. Utilizing real-world network traffic datasets, the developed deep learning-based network anomaly detection system enhances the capability to detect and mitigate cyber threats, thereby reinforcing the security and resilience of smart manufacturing systems. The practical benefits of this enhanced cyberattack detection system include improved operational reliability, reduced downtime, and the protection of critical assets in real-world smart manufacturing settings.

An IoT-based GNSS platform for infrastructure monitoring

Abstract. In recent years, mining operators have adopted Information and Communications Technology (ICT) for monitoring and inspection operations but archaic/manual processes to collect and analyse data are still in use, thus making the protection of mining critical assets a costly and highly complex problem, reducing the capabilities of the monitoring system to trigger automatic alarms. Within the SEC4TD project, a low-cost IoT-based GNSS positioning device is developed, with the aim to provide accurate absolute positions of infrastructures. The solution includes the use of a two bands (L1, L2) GNSS receiver, long power autonomy and RTK correction on edge nodes. The paper describes the first prototype and the initial testing to evaluate its positional precision. A long term evaluation over 15 days is performed including a comparison with a high-end receiver. Lastly, field conditions are mimicked by reducing to 60 the number of epochs used in estimating the position each hour allowing for continuous monitoring of the infrastructure of interest.

Оцінювання та підвищення кібербезпеки топології об’єктів критичної інформаційної інфраструктури в глобальному кіберпросторі

Risk-informed approaches to the organization of the topology of critical information infrastruc-ture during its design and modernization are proposed. Recommendations are provided to in-crease the protection of critical information assets from such attacks, the vector of which is ex-ternal connections (connections in cyberspace) of the critical information infrastructure object (CII), and references are also provided to good practices for assessing information security risks. The presented recommendations describe additional measures that detail or complement more general procedures performed in the information security cycle.

БЕЗПЕЧНИЙ ДОСТУП ДО СЕРВЕРІВ ІНФОРМАЦІЙНИХ СИСТЕМ, ЗАБЕЗПЕЧЕНИЙ ML-МОДЕЛЛЮ ДЛЯ БЛОКУВАННЯ ШКІДЛИВИХ ЗАПИТІВ

The article presents a detailed exploration of using the k-Nearest Neighbors (KNN) algorithm to classify and identify various types of cyberattacks, particularly SQL Injection (SQLi) attacks, within SCADA (Supervisory Control and Data Acquisition) systems. This work addresses the need to enhance server infrastructure security in SCADA systems by mitigating the risks posed by harmful requests, such as SQL injections. SCADA systems are crucial in managing industrial processes, making their servers prime cyberattack targets. Attackers often exploit vulnerabilities in server applications by injecting malicious requests through input fields or URLs, potentially gaining access to sensitive data or disrupting system operations. To address this issue, the study proposes a machine learning-based approach using the k-nearest neighbors (KNN) algorithm to detect and block harmful SQL requests. The KNN algorithm is employed to classify and identify different types of cyberattacks by comparing new attack attempts with previously observed attack patterns. By analyzing specific attributes related to each attack, the KNN method evaluates the level of threat based on proximity metrics. The proposed approach helps classify SQL injection attempts, which involve manipulating SQL code to bypass authentication or extract unauthorized data. The study demonstrates how KNN can effectively distinguish harmful SQL requests from benign ones by calculating the Euclidean distance between the new attack and historical cases. Furthermore, the article emphasizes the importance of implementing rapid and accurate detection methods for protecting server infrastructure in industrial environments. The KNN algorithm, in this context, offers a flexible and efficient solution as it adapts to various attack scenarios, improving the overall resilience of SCADA systems to cyber threats. The study’s findings contribute to the ongoing efforts in cybersecurity, focusing on integrating machine learning models to strengthen the protection of critical assets in industrial control systems. This work aims to develop protection tools for server-based industrial control systems used in SCADA systems against dangerous requests based on SQL injections, using an ML-trained model for blocking harmful requests through the k-nearest neighbors method.

Building design and selection for protection of critical assets

AbstractMission Critical Buildings (MCB) are buildings that must remain operational in the event of a crisis to minimize risks due to asset damage, business interruption, and personnel impact. MCBs in processing facilities face operational hazards including explosions, fragments, fires, and toxic events. In the CSB's investigation report of the Philadelphia Energy Solutions Refinery incident, a recommendation was included for the API to update its standard to “require protection of critical safeguards and associated control system components from fire and explosion hazards, including radiant heat and flying projectiles.” This recommendation, if implemented, would require facilities to ensure MCBs are Multi‐hazard Resistant Buildings (MRBs) able to withstand a range of potential impacts. This paper details the key design characteristics of MRBs to protect critical assets in industrial processing facilities such as critical safeguards and control systems; emergency response equipment; people critical to operations and emergency response; or people located in buildings near processing units. Key concepts of protective building design are introduced, including the response of different building materials to hazards common in processing facilities. These concepts are then examined to illustrate how building response translates to human and equipment vulnerability.

Reverse Blocking Over Current Busbar Protection Scheme Based on IEC 61850 Architecture

Substation Automation System (SAS) is currently in a matured state of technology that shall facilitate transformational changes from conventional protection scheme. IEC 61850 protocol is considered as the crux of digital SAS due to its multifunction features that include seamless communication, ability to integrate various intelligent electronic devices, potential for improved real-time condition monitoring, reliable protection, and control of critical electrical assets. Because the application of IEC 61850 in SAS is relatively new and has not fully implemented in many substations yet, further feasibility studies using multivendor equipment to assess its performance under different operating conditions is imperative. In this article, a practical reliable and efficient reverse blocking over current bus bar protection scheme based on IEC 61850 is implemented and tested. Also, a comparison of digital SAS and conventional protection scheme is presented to highlight the superiority of the former one. Experimental results attest the reliability and effectiveness of the proposed digital protection scheme along with the accuracy and security of transmitting data packets using sampled values and generic objective-oriented substation event communication protocols adopted by IEC 61850.

Impact of cyberspace on the cybersecurity of critical national assets infrastructures in Nigeria: A review of education and financial sectors

Unprepared with a fragile digital infrastructures, and hurriedly tossed into the depth of the cyberspace in the Fourth and Fifth Industrial Revolutions (4IR and 5IR) by Covid-19 pandemic measures, of lockdown and needs for remote learning. The educational sector became the most vulnerable; with streams of cyber-attacks stalling virtual classes and compromising data integrity, of which the financial sector was not exempted, despite the evolvement of cyber insurance policy. The financial end users are aggravated and left at the mercy of internet fraudsters called “yahoo-yahoo” boys, coupled with hacking of SWIFT, crypto currency thefts, and Nations’ Central Banks falling into cyber-attacks, thus leaving no unconquered space for cybercriminals, even as cyber literacy and security are siloed away under stand-alone arrangements despite the interconnectedness of the cyberspace. It was against this background, that this study leverages on Theory of Endogenous Growth Model to interrogate impact of cyberspace on the protection of critical national assets and infrastructures in Nigeria. The study deconstruct national assets into education and financial sectors to assess the existing impact. This study adopts qualitative research design using exploratory research design of publicly available archive documents. Empirical evidence from study revealed that cyberspace has expanded the virtual learning horizon while cyber attacks still remain on the minimal. Findings that emanate from this study revealed cyberspace has positively impacted on the Nigeria Financial sector through financial inclusion and transaction conveniences while the damaging effect of cyberattacks remained largely covered up. The study recommends that all players in the educational sector should invest widely in cybersecurity as days of imminent cyberattacks is on the horizon as seen evolving in developed clime. Study also recommend that government should firm up cyberspace policy, and inject collectivism into cyber security plans of sectors as an improvement on the present stand alone security by banks in Nigeria.

Deployment of Artificial Intelligence with Bootstrapped Meta-Learning in Cyber Security

Cybersecurity is an extensive and vivacious domain in the commercial progression of the ecosphere. By up-to-date inhabitants, networking settings and assets, cybersecurity fits with the exigent task to realize the necessities of the imminent populace. Intelligent cybersecurity / intellectual smart cybersecurity has risen as a pioneering tool to deal with latest ambiguities in programmed cybersecurity enduring capability by bringing together Artificial Intelligence (AI) in Cybersecurity Computerization. The mechanism that enterprises in this cutting-edge technology handles the mechanism capability to acquire via depleting Bootstrapped Meta-learning and reinforced with rewards as Supreme Cybersecurity vintages, besides least resource utilizations as well as time limits. AI empowered cybersecurity technology is a vital constituent of the imminent cybersecurity revolution ahead. During this operation, a proficient computerization of AI application in the arena of cybersecurity sustenance is ready for attaining the supreme output welfares as results, also inhibiting the real assets. Setting the precise real-time issues are trailed by cracking it for affluence and escalation or magnification of cybersecurity thus by prominent universal preeminent impending cybersecurity. A meta-learning/AI-based automated security strategy is vital in the protection of critical infrastructure, users and assets disinclined to outbreaks.

Evaluating the Security Posture and Protection of Critical Assets of Industrial Control Systems in Zambia

The number of successful attacks on vital infrastructure has increased, as has the sophistication of the attacks. Many cybersecurity strategies include traditional best practices, but they frequently overlook organizational circumstances and unique critical infrastructure protection requirements. The goal of this qualitative multiple case research was to look into the cybersecurity tactics employed by IT managers and compliance officers to protect critical infrastructure from cyber threats. The participants in this study were IT managers and compliance officials from four Zambian case organizations. The conceptual framework was based on the routine activity theory published by criminologists Cohen and Felson in 1979. Interviews with two IT managers, three compliance officers, and 25 papers relating to cybersecurity and policy governance were used to gather data. Four significant themes emerged from data triangulation: the need for a robust worker training program, prioritizing infrastructure resiliency, the importance of security awareness, and the importance of organizational leadership support and investment. This research uncovered essential tactics that can help OT and compliance professionals enhance their cybersecurity strategy, which can help reduce successful assaults on critical infrastructure. The study findings will contribute to positive social change through an exploration and contextual analysis of cybersecurity strategy with situational awareness of OT practices to enhance cyber threat mitigation and inform business processes.

A High-Impact Data-Driven Decision-Making Model for Integrating Cutting-Edge Cybersecurity Strategies into Public Policy, Governance, and Organizational Frameworks

The increasing prevalence of cyber threats in the digital age underscores the urgent need for innovative and data-driven approaches to cybersecurity. This study proposes a high-impact decision-making model designed to integrate cutting-edge cybersecurity strategies into public policy, governance, and organizational frameworks. The model emphasizes leveraging big data, artificial intelligence (AI), and advanced analytics to inform policy design, risk assessment, and strategic planning in diverse institutional contexts. Key components of the model include real-time data aggregation, predictive analytics, and machine learning algorithms to identify and mitigate cyber risks proactively. By incorporating advanced threat intelligence and risk quantification, the model enables stakeholders to prioritize vulnerabilities, allocate resources effectively, and enhance resilience against evolving cyber threats. The framework also integrates multi-stakeholder collaboration, ensuring alignment between public and private sector efforts in addressing cybersecurity challenges. This model is adaptable across various governance levels and organizational structures, providing actionable insights to policymakers, regulators, and organizational leaders. It aligns with global cybersecurity standards and emphasizes compliance with frameworks such as the NIST Cybersecurity Framework, GDPR, and ISO/IEC 27001. The research highlights the importance of embedding cybersecurity into governance processes and organizational strategies to foster a culture of security and accountability. Pilot studies demonstrate the model's applicability in enhancing decision-making processes, reducing response times, and improving risk mitigation outcomes. Case studies from public and private sectors reveal the model’s capacity to drive more informed and adaptive policy frameworks while promoting operational efficiency and trust among stakeholders. This study contributes to the evolving field of cybersecurity by providing a scalable and replicable approach for integrating data-driven strategies into policy and governance. By bridging the gap between technological innovation and institutional readiness, the proposed model equips policymakers and organizations to navigate complex cyber landscapes effectively, ensuring the protection of critical infrastructure, data, and digital assets.

A High-Impact Data-Driven Decision-Making Model for Integrating Cutting-Edge Cybersecurity Strategies into Public Policy, Governance, and Organizational Frameworks

The increasing prevalence of cyber threats in the digital age underscores the urgent need for innovative and data-driven approaches to cybersecurity. This study proposes a high-impact decision-making model designed to integrate cutting-edge cybersecurity strategies into public policy, governance, and organizational frameworks. The model emphasizes leveraging big data, artificial intelligence (AI), and advanced analytics to inform policy design, risk assessment, and strategic planning in diverse institutional contexts. Key components of the model include real-time data aggregation, predictive analytics, and machine learning algorithms to identify and mitigate cyber risks proactively. By incorporating advanced threat intelligence and risk quantification, the model enables stakeholders to prioritize vulnerabilities, allocate resources effectively, and enhance resilience against evolving cyber threats. The framework also integrates multi-stakeholder collaboration, ensuring alignment between public and private sector efforts in addressing cybersecurity challenges. This model is adaptable across various governance levels and organizational structures, providing actionable insights to policymakers, regulators, and organizational leaders. It aligns with global cybersecurity standards and emphasizes compliance with frameworks such as the NIST Cybersecurity Framework, GDPR, and ISO/IEC 27001. The research highlights the importance of embedding cybersecurity into governance processes and organizational strategies to foster a culture of security and accountability. Pilot studies demonstrate the model's applicability in enhancing decision-making processes, reducing response times, and improving risk mitigation outcomes. Case studies from public and private sectors reveal the model’s capacity to drive more informed and adaptive policy frameworks while promoting operational efficiency and trust among stakeholders. This study contributes to the evolving field of cybersecurity by providing a scalable and replicable approach for integrating data-driven strategies into policy and governance. By bridging the gap between technological innovation and institutional readiness, the proposed model equips policymakers and organizations to navigate complex cyber landscapes effectively, ensuring the protection of critical infrastructure, data, and digital assets.

FACTORS OF ENSURING ECONOMIC SECURITY IN THE PROCESS OF INNOVATIVE DEVELOPMENT OF ENTREPRENEURSHIP

Topicality. The urgency of our research is due to the fact that business security management creates a basis for innovative development of entrepreneurship. Ensuring economic security is a factor of innovative development of entrepreneurship, of advanced business management techniques using, of business efficiency increasing, and the world's production quality standards achieving. Aim and tasks. The main purpose of the research is to develop theoretical and scientific-methodological statements for improving the business security management as a part of the process of innovative development of entrepreneurship in the context of ensuring the protection of all systems of the business entity from destructive influences, both internal and external factors, threats and dangers. Research results. The idea is substantiated that business security management is designed to promote the continuity of the process of identifying critical, in terms of innovative development, assets and possible threats to these assets, as well as reducing any vulnerabilities through careful analysis and implementation of effective countermeasures to achieve an optimal level of protection of critical assets. It is established that regardless of the type of organization, in the assessment of existing threats and dangers to the innovative development of entrepreneurship should be indicated: firstly, which critical assets of the business entity need protection; secondly, what type of information and what means are needed to protect each asset; finely, how the loss, damage, or destruction of a critical asset will affect the innovative development of the business entity and its mission. The results indicate that the business security management should include: firstly, assessment of threats and dangers to innovative business development; secondly, vulnerability assessment and risk assessment, which allow decision-makers to ensure the economic security of business activities, to give priority to asset protection protocols; and finally, specific recommendations on how to block opportunities for enemy attacks and how to protect specific assets in terms of innovative development. Conclusion. The results of the study allowed us to conclude that in the context of innovative development the business security management is the key to the long-term existence of economic entities and the formation of competitive advantages of their products in the market of goods and services. Business security management helps to eliminate additional threats and dangers that may be associated with innovative business development. Thus, only effective management of business security can guarantee the protection of all the business entity systems from destructive influences, both internal and external factors, to prevent and eliminate threats, contributing to the continuity of innovative development.

Analysis of Selected Assets against the Extraordinary Loads

The current security situation in the world creates pressure to improve the pro-tection of critical infrastructure assets against negative events, such as bomb attacks, industrial accidents, explosions, or fire. The research at the Faculty of Security Engineer-ing is focusing on such extraordinary loads. The present paper analyses selected assets against extraordinary load and describes their experimental testing.

Cyber Warfare Trends, Tactics and Strategies: Lessons for Pakistan

With the advent of the digital revolution, computer security has gradually evolved from a technology problem to a business and safety problem. Unlike conventional warfare, cyber warfare is inexpensive, effective and obscure, which in case of conflict, offers nation states a combination of cyber tools such as espionage, subversion, disinformation, and propaganda. Cyber warfare may prove decisive in many international conflicts in the future. This paper discusses the evolution of cyber-attack surfaces, adversaries and next generation cyber-attacks, and illustrates the security risks posed by the technological revolution and its impacts. It further discusses the potential solutions, and measures which the Government of Pakistan (GoP) may take to build effective detection and response cyber warfare capabilities. The GoP should consolidate the available cluster of skills and technology to establish a national agency mandated to conduct cybersecurity for efficient critical asset protection and effective response to any kind of cyber-attack.

A Review of Marine Current Energy and Types of Energy using MOORA Method

National security, public safety, Social economic security, lifestyle because of its importance Critical infrastructure plays a significant role in countries. Of infrastructures Depending on the importance, It is possible to prevent these risks from becoming incidents Risk analysis is essential. The main objective of this thesis is to provide a more secure, to build secure and highly resilient critical infrastructure, with the aim of overcoming the limitations of the traditional approach to operation and control is to present a developed framework. The proposed framework is for effects on value at risk Routine by introducing new parameters Extends RAMCAP (Risk Analysis and Management for Critical Asset Protection). The complexity of the problem and According to the inherent uncertainty, this research MCDM EDAS Adopts multiple criteria as a decision-making technique. Capacity of the model for risk ranking of critical infrastructures and to explain performance Case analysis is implemented. The proposed model shows significant improvement as compared to conventional RAMCAP.

Integrated protection of industrial control systems from cyber-attacks: the ATENA approach

Industrial and Automation Control systems traditionally achieved security thanks to the use of proprietary protocols and isolation from the telecommunication networks. Nowadays, the advent of the Industrial Internet of Things poses new security challenges. In this paper, we first highlight the main security challenges that advocate for new risk assessment and security strategies. To this end, we propose a security framework and advanced tools to properly manage vulnerabilities, and to timely react to the threats. The proposed architecture fills the gap between computer science and control theoretic approaches. The physical layers connected to Industrial Control Systems are prone to disrupt when facing cyber-attacks. Considering the modules of the proposed architecture, we focus on the development of a practical framework to compare information about physical faults and cyber-attacks. This strategy is implemented in the ATENA architecture that has been designed as an innovative solution for the protection of critical assets.

Cyber-Resilience: Seven Steps for Institutional Survival

No enterprise will ever be 100% secure. There are just too many threats. This article presents seven practical steps to achieving cyber-resilience. Cyber resilience is not a traditional defensive stance. It requires a change in the way organizations approach security of its information and communication technology (ICT) asset base. Cyber resilience is integrated into the “bones” of the organization and requires the organization to develop a well-defined, explicit architecture of controls to ensure cyber resiliency. The controls assure provable protection of critical ICT assets and their various interdependencies from every form of electronic, human and physical threat; inside and outside the enterprise’s eco-system. Cyber-resilient architectures make attacks less likely to succeed, minimize the consequences when they do, increase the work-factor cost and uncertainty for the adversary, and possibly act as a deterrent against future attacks. Cyber resilience is enforced as an organizational condition rather than a deployed set of explicit countermeasures. This goal requires that a robust set of concrete controls are embedded in the enterprise architecture. Effective implementation of a cyber-resilient enterprise architecture requires strategic vision. It also requires day-to-day engagement across the enterprise to ensure that the controls that enable cyber resilience are effective.

Risk and Resilience Analysis for Highway Assets

Transportation agencies own tens of thousands of assets, providing essential mobility and economic services to the communities they serve. Moving Ahead for Progress in the 21st Century and subsequent legislation require asset managers to implement risk-based asset management. A discussion is presented on the application of one quantitatively based framework—the American Society of Mechanical Engineers Innovative Technology Institute's Risk and Resilience Analysis and Management for Critical Asset Protection—for analyzing risks posed by physical threats to highway transportation systems and assets. The application of this particular risk analysis framework by the Colorado Department of Transportation following the 2013 floods is recounted; the analysis was used to support requests for federal emergency response funding. Finally, the potential benefits of such analysis for highway transportation project planning and strategic planning are also examined.

A model-driven approach for vulnerability evaluation of modern physical protection systems

Modern physical protection systems integrate a number of security systems (including procedures, equipments, and personnel) into a single interface to ensure an adequate level of protection of people and critical assets against malevolent human actions. Due to the critical functions of a protection system, the quantitative evaluation of its effectiveness is an important issue that still raises several challenges. In this paper we propose a model-driven approach to support the design and the evaluation of physical protection systems based on (a) UML models representing threats, protection facilities, assets, and relationships among them, and (b) the automatic construction of a Bayesian Network model to estimate the vulnerability of different system configurations. Hence, the proposed approach is useful both in the context of vulnerability assessment and in designing new security systems as it enables what-if and cost–benefit analyses. A real-world case study is further illustrated in order to validate and demonstrate the potentiality of the approach. Specifically, two attack scenarios are considered against the depot of a mass transit transportation system in Milan, Italy.