Cybersecurity Framework Research Articles

Harnessing artificial intelligence (AI) for cybersecurity: Challenges, opportunities, risks, future directions

The integration of artificial intelligence (AI) into cybersecurity has brought about transformative advancements in threat detection and mitigation, yet it also introduces new vulnerabilities and potential threats. This research exploration systematically investigates the critical issues surrounding AI within cybersecurity, focusing on specific vulnerabilities and the potential for AI systems to be exploited by malicious actors. The research aims to address these challenges by swotting and analyzing existing methodologies designed to mitigate such risks. Through a detailed exploration of modern scientific research, this manuscript identifies the dual-edged impact of AI on cybersecurity, emphasizing both the opportunities and the dangers. The findings highlight the need for strategic solutions that not only enhance digital security and user privacy but also address the ethical and regulatory aspects of AI in cybersecurity. Key contributions include a comprehensive analysis of emerging trends, challenges, and the development of AI-driven cybersecurity frameworks. The research also provides actionable recommendations for the future development of robust, reliable, and secure AI-based systems, bridging current knowledge gaps and offering valuable insights for academia and industry alike.

Transnational Cyber Governance for Risk Management in the Gas Sector: Exploring the Potential of G7 Cooperation

At the Group of Seven (G7) summit held on 13–15 June in 2024, the Group’s leaders committed to establishing a collective cyber security framework and reinforcing the work of the cyber security working group to manage the risks targeting energy systems. Likewise, oil and electricity, and natural gas rely on complex and interdependent technologies and communication networks from production to consumption. The preparedness to handle cyber security threats in the energy infrastructures among decision makers, planners, and the industry in a concerted manner signifies that cyber security is becoming more appreciated. Therefore, considering the ambition and achievement of the G7 countries towards energy and cyber sovereignty, this paper’s focus and research question aims to explore the potential existence of the cyber governance alliance in the gas subsector within the G7. The objective of this paper is twofold. First, it explores the potential of the G7, the world’s seven largest advanced economies, to lead on a nascent cyber governance for risk management in the gas sector. The qualitative analysis conducted through the institutional analysis and design method examines up-to-date data involving mainly state actors. Second, by drawing on LNG, one of the world’s fastest growing energy types in the coming decades, the paper points out the need for further research on the transnational governance operating through public–private engagement to address the cyber risks to gas systems. While the paper makes an empirical contribution to the field of security governance and a practical contribution to security consulting, its limitations rely on the necessity to also conduct a quantitative enquiry, which would necessitate, among others, a review of the literature in the G7 countries, and a group of researchers from academia and practitioners to obtain a sense of the cyberspace in the energy reality.

Cybersecurity in Prognostics and Health Management

PHM continues to show its value by improving operational efficiencies, increasing safety, reducing downtime, and decreasing cost of operations. PHM technologies are therefore not only being deployed as retrofit solutions but are being integrated into new systems as standard practice. Deployment covers areas such as medical equipment, nuclear power plants, aeronautics applications, oil and gas, mining, and many others. As the impact of PHM increases, it is imperative to also consider the potential vulnerabilities that are being exposed. Hackers have famously used Supervisory Control and Data Acquisition (SCADA) and Programmable Logic Controller (PLC) systems to sabotage industrial facilities. As such, it is important to understand the exposure to malfeasance to ensure that PHM does not end up being the enabling mechanism for unauthorized access to the system it is meant to keep in running order. It is also important to understand the measures that need to be taken to avoid or respond to an attack. These range from extensive penetration testing to conducting extensive counter-social engineering training, setting up a PHM-specific CERT plan and team in place. This paper discusses various threats that are emerging and that may have to be considered when designing a PHM solution. Additionally, the NIST cybersecurity framework is discussed in the context of PHM. Finally, this paper looks at the diagnostic capabilities of PHM systems to detect cyber security attacks and to contain these threats.

Cyber-Securing Medical Devices Using Machine Learning: A Case Study of Pacemaker

This study aims to enhance the cybersecurity framework of pacemaker devices by identifying vulnerabilities and recommending effective strategies. The objectives are to pinpoint cybersecurity weaknesses, utilize machine learning to predict security breaches, and propose countermeasures based on analytical trends. The literature review highlights the transformation of pacemaker technology from basic, fixed-rate devices to sophisticated systems with wireless capabilities, which, while improving patient care, also introduce significant cybersecurity risks. These risks include unauthorized entry, data breaches, and life-threatening device malfunctions. The methodology in this study utilizes a quantitative research approach using the WUSTL-EHMS-2020 dataset, which includes network traffic features, patients' biometric features, and attack label. The step-by-step method of machine learning prediction includes data collection, data preprocessing, feature engineering, and models’ training using Support Vector Machines (SVM) and Gradient Boosting Machines (GBM). The implementation results used evaluation metrics like accuracy, precision, recall, and F1 score to show that GBM model outperformed the SVM model. The GBM model achieved higher accuracy of 95.1% compared to 92.5% for SVM, greater precision of 99.6% compared to 96.7% for SVM, better recall of 94.9% compared to 42.7% for SVM, and a higher F1 score of 76.3% compared to 59.0% for SVM, making GBM model more effective in predicting cybersecurity threats. This study concludes that GBM is an effective machine learning model for enhancing pacemaker cybersecurity by analyzing network traffic and biometric data patterns. Future recommendations for improving the pacemaker cybersecurity include implementing GBM model for threat predictions, integration with existing security measures, and regular model updates and retraining.

Assessment of Cybersecurity Risks in Digital Twin Deployments in Smart Cities

Digital Twin (DT) technology has become a cornerstone of modern smart city infrastructure, providing real-time insights and operational efficiencies by creating a virtual replica of physical systems such as traffic networks, energy grids, and public services. While these advancements enable optimized urban management and improved decision-making, they also present new cybersecurity challenges that can potentially jeopardize the safety and reliability of critical infrastructures. This study addresses the cybersecurity risks associated with Digital Twin deployments in smart cities, focusing on threats such as unauthorized access, data manipulation, and hijacking of the DT models, which could result in service disruptions and compromise public safety. The research employs a comprehensive risk assessment methodology based on the NIST Cybersecurity Framework, where potential risks are identified, evaluated, and prioritized according to their severity and likelihood of occurrence. To mitigate these risks, a multi-layered security framework was developed, incorporating encryption mechanisms, robust access control, and an Artificial Immune System (AIS)-based anomaly detection model. The framework was tested through a simulated case study on a smart transportation system within a smart city environment, demonstrating its effectiveness in preventing data tampering and detecting unauthorized access. The results indicate that the proposed security model reduced data manipulation incidents by 35%, decreased response times for threat detection by 25%, and improved overall system resilience by 40%. These findings underscore the critical need for proactive cybersecurity strategies in ensuring the secure and resilient deployment of Digital Twin technologies in smart cities. The study concludes by emphasizing the importance of continuous security monitoring and adaptive threat management to safeguard smart city ecosystems from evolving cyber threats

Zero Trust Cybersecurity: Procedures and Considerations in Context

In response to the increasing complexity and sophistication of cyber threats, particularly those enhanced by advancements in artificial intelligence, traditional security methods are proving insufficient. This paper provides an overview of the zero-trust cybersecurity framework, which operates on the principle of “never trust, always verify” to mitigate vulnerabilities within organizations. Specifically, this paper examines the applicability of zero-trust principles in environments where large volumes of information are exchanged, such as schools and libraries, highlighting the importance of continuous authentication (proving who users are within the network), least privilege access (providing only access to what users specifically need), and breach assumption (assuming a breach has or will occur and thus operating to limit the spread through the use of multiple checkpoints throughout the network). The analysis highlights avenues for future research that may help preserve the security of vulnerable organizations.

RETRACTED: Alrubaiq, A.; Alharbi, T. Developing a Cybersecurity Framework for e-Government Project in the Kingdom of Saudi Arabia. J. Cybersecur. Priv. 2021, 1, 302–318

RETRACTED: Alrubaiq, A.; Alharbi, T. Developing a Cybersecurity Framework for e-Government Project in the Kingdom of Saudi Arabia. J. Cybersecur. Priv. 2021, 1, 302–318

Advancements in cybersecurity and machine learning: A comprehensive review of recent research

The convergence of cybersecurity and machine learning (ML) has emerged as a pivotal area of research, promising significant advancements in the protection of digital assets. This paper presents a comprehensive review of recent research focused on the integration of machine learning techniques within cybersecurity frameworks. We analyze key developments, including anomaly detection, threat intelligence, and automated response systems. The review highlights both the benefits and challenges of employing ML in cybersecurity, such as enhanced threat detection capabilities and potential issues related to adversarial attacks. By synthesizing findings from various studies, this paper aims to provide a nuanced understanding of how machine learning is transforming cybersecurity practices and suggest future research directions to address existing gaps and enhance system robustness.

A Comprehensive Review of Large Language Models in Cyber Security.

In response to the escalating complexity of cyber threats and the rapid expansion of digital environments, traditional detection models are proving increasingly inadequate. The advent of Large Language Models (LLMs) powered by Natural Language Processing (NLP) represents a transformative advancement in cyber security. This review explores the burgeoning landscape of LLM applications in cyber security, highlighting their significant potential across various threat detection domains. Recent advancements have demonstrated LLMs' efficacy in enhancing tasks such as cyber threat intelligence, phishing detection, anomaly detection through log analysis, and more. By synthesizing recent literature, this paper provides a comprehensive overview of how LLMs are reshaping cyber security frameworks. It also discusses current challenges and future directions, aiming to guide researchers and practitioners in leveraging LLMs effectively to fortify digital defences and mitigate evolving cyber threats

Does Cyber Insurance Promote Cyber Security Best Practice? An Analysis Based on Insurance Application Forms

The significant rise in digital threats and attacks has led to an increase in the use of cyber insurance as a cyber risk treatment method intended to support organisations in the event of a security breach. Insurance providers are set up to assume such residual risk, but they often require organisations to implement certain security controls a priori to reduce their exposure. We examine the assertion that cyber insurance promotes cyber security best practice by conducting a critical examination of cyber insurance application forms to determine how well they align with ISO 27001, the NIST Cybersecurity Framework and the UK’s Cyber Essentials security standards. We achieve this by mapping questions and requirements expressed in insurance forms to the security controls covered in each of the standards. This allows us to identify security controls and standards that are considered—and likely most valued—by insurers and those that are neglected. We find that while there is some reasonable coverage across forms, there is an underrepresentation of best practice standards and controls generally, and particularly in some control areas (e.g., procedural/governance controls, incident response and recovery).

Cybersecurity in the Age of IoT: Business Strategies for Managing Emerging Threats

The quick spread of the Internet of Things (IoT) has essentially changed industries by linking devices, systems, and data. This expansion has, in turn, generated exceptional cybersecurity vulnerabilities, which introduces an urgent requirement for detailed security solutions. This paper analyzes new cybersecurity risks present in the IoT ecosystem and looks into successful business approaches for managing these threats. Using a thorough assessment of current literature, practical case studies, and extensive data analysis, the study discovers essential weaknesses in IoT devices, networks, and infrastructure. The method used collects information from latest incidents related to IoT breaches and evaluates several business strategies designed to meet these challenges. Findings imply that using advanced technologies like artificial intelligence (AI) and machine learning (ML) in monitoring, in conjunction with collaborative cybersecurity frameworks, strongly enhances the security of the IoT. The originality of this research is in its thorough review of the evolving threat landscape and its practical recommendations for enterprises to advance their Internet of Things security position in a quickly changing environment.

Integrating AI with aviation cybersecurity: The strategic role of human resources<sup></sup>

The escalating complexity of cyber threats in aviation highlights the crucial need to integrate advanced technologies and strategic human resource management. This study delved into incorporating artificial intelligence (AI) in aviation cybersecurity, explicitly focusing on the strategic role of human resources (HR) in supporting these endeavours. Semi-structured interviews with eight industry experts from Turkey were analysed using NVivo to identify critical themes such as HR's involvement in cybersecurity, challenges in AI implementation, and the significance of cultural integration and interdepartmental collaboration. Sentiment analysis with Python's TextBlob indicated high positivity towards AI and strategic HR involvement. The findings underscored the necessity for continuous education, strategic recruitment, and resilient cybersecurity frameworks, emphasising AI's transformative impact on real-time threat detection and predictive analytics. The research offered valuable insights and recommendations for enhancing aviation cybersecurity, highlighting the essential role of HR and the advantages of AI integration.

Взгляды военно-политического руководства США на защиту критически важных объектов от угроз кибернетического воздействия

The study examines the potential threats of cybernetic impact on critical U.S. facilities that support the activities of the armed forces, and the measures of the American administration to identify and neutralize them. Based on the results of the analysis, it was concluded that the destructive impact on critical infrastructure undermines the military potential of the state and the combat capability of the armed forces. The multidimensional and cross-border nature of threats objectively necessitates the search for ways to prevent and eliminate such threats, as well as the development of interdepartmental and international cooperation in combating cyber threats. This requirement places a burden on state and military leaders to possess knowledge not only in the realm of military security but also in the field of national cybersecurity. Significant cross-industry risks are associated with energy infrastructure, particularly with the supply of gas to electricity producers. The most vulnerable parts of infrastructure are the energy systems that are utilized to supply electricity to military bases and other U.S. military facilities located abroad. A crucial aspect of ensuring the cyber security of energy infrastructure is the regulation of the supply chain for information technology products. Awareness of vulnerabilities within the cybersecurity framework of the U.S. defense infrastructure can be leveraged to refine the list of critical targets of a potential adversary and inform the planning and execution of information operations by the General Staff of the Armed Forces of the Russian Federation.

From Embodied Abuse to Mass Disruption : Generative, Inter-Reality Threats in Social, Mixed-Reality Platforms

Extended Reality (XR) platforms can expose users to novel attacks including embodied abuse and/or AI attacks-at-scale. The expanded attack surfaces of XR technologies may expose users of shared online platforms to psychological/social and physiological harms via embodied interactions with potentially millions of other humans or artificial humans, causing what we define as an inter-reality attack. The past twenty years have demonstrated how social and other harms (e.g. bullying, assault and stalking) can and do shift to digital social media and gaming platforms. XR technologies becoming more mainstream has led to investigations of ethical and technical consequences of these expanded input surfaces. However, there is limited literature that investigates social attacks, particularly toward vulnerable communities, and how AI technologies may accelerate generative attacks-at-scale. This paper employs human-centred research methods and a harms-centred Cybersecurity framework to co-design a testbed of socio-technical attack scenarios in XR social gaming platforms. It uses speculative fiction to further extrapolate how these could reach attacks-at-scale by applying generative AI techniques. It develops an Inter-Reality Threat Model to outline how actions in virtual environments can impact on the real-world. As AI capability continues to rapidly develop, this paper articulates the urgent need to consider a future where XR-AI attacks-at-scale could become commonplace.

Development of cybersecurity framework for FinTech innovations: Bahrain as a case study

Development of cybersecurity framework for FinTech innovations: Bahrain as a case study

A collaborative cybersecurity framework for higher education

Purpose The purpose of this paper is to present the educational computer emergency response team (EduCERT) framework, an integrated response mechanism to bolster national cybersecurity through collaborative efforts in the higher education sector. The EduCERT framework addresses this gap by enhancing cyber security and mitigating cybercrime through collaborative incident management, knowledge sharing and university awareness campaigns. Design/methodology/approach The authors propose an EduCERT framework following the design science methodology. The framework is developed based on literature and input from focus group experts. Moreover, it is grounded in the principles of the technology-organization-environment framework, organizational learning and diffusion of innovations theory. Findings The EduCERT has eight components: infrastructure, governance, knowledge development, awareness, incident management, evaluation and continuous improvement. The framework reinforces national cybersecurity through cooperation between universities and the National Computer Emergency Response Team. The framework has been implemented in Jordan to generate a cybersecurity foundation for higher education. Evaluating the EduCERT framework’s influence on national cybersecurity highlights the importance of adopting comprehensive cyber-security policies and controls. The framework application shows its relevance, effectiveness, adaptability and alignment with best practices. Research limitations/implications Despite the impact of applying the framework in the Jordanian context, it is essential to acknowledge that the proposed EduCERT framework’s practical implementation may encounter challenges specific to diverse international educational environment sectors. However, framework customization for global applicability could address varied educational institutions in other countries. Practical implications Furthermore, the proposed EduCERT framework is designed with universal applicability that extends beyond the specific country’s context. The principles and components presented in the framework can serve as valuable design advice for establishing collaborative and resilient cybersecurity frameworks in educational settings worldwide. Therefore, the research enhances the proposed framework’s practical utility and positions it as an invaluable contribution to the broader discourse on global cybersecurity in academia. Originality/value This paper enhances national cybersecurity in the higher education sector, addressing the need for a more integrated response mechanism. The EduCERT framework demonstrates its effectiveness, adaptability and alignment with best practices, offering valuable guidance for global educational institutions.

Drafting a Cybersecurity Standard for Outer Space Missions: On Critical Infrastructure, China, and the Indispensability of a Global Inclusive Approach

Despite limited progress within international institutions, the need for articulating a regulatory framework for cyber operations in outer space is becoming a pressing concern. One precondition for regulation is to share cybersecurity and outer-space common terminology that can inform the negotiation of standards, policies and laws. While the UN Institute for Disarmament Research has recently issued a baseline policy glossary, binding technical definitions are missing, and the lack of a binding international cybersecurity regime adds to the obsolescence of a binding outer-space regime tracing back to half a century ago. As the IEEE SA embarks on the drafting of the first-ever technical standard for cybersecure-by- design outer-space missions, scoping and conceptual challenges abound. Technical standards are US-centred, non-binding, engineering-intensive exercises, where lawyers and Asian jurisdictions are only marginally involved; nevertheless, as China’s framework for cybersecurity is refined and its involvement in outer-space policing deepens, its disengagement from Western-driven standard-setting bodies appears unsustainable. Drawing on the specific challenge of defining what makes a cyber system ‘mission-critical’, I expose the necessity to examine how domestic cybersecurity laws from a diverse range of States identify ‘critical’ information infrastructure. Generalising therefrom, I advocate a jurisdictionally inclusive process that combines American supremacy in technical standard-setting for outer-space missions with Chinese normative contributions to cybersecurity regulation, including on data localisation and mandatory multilevel cyber-hygiene requirements. I further argue that involving legal experts from a diverse range of jurisdictions and sociolegal cultures may enhance the global reception of standardisation outputs, thus securing higher degrees of voluntary compliance therewith. This could foster cooperation and promote regional and global satellite cybersecurity.

EFFECT OF DATA PROTECTION FRAMEWORKS AGAINST CYBERCRIMES ON CYBER SECURITY IN NIGERIA

The paper Effect of Data Security Frameworks against Cybercrimes and Cyber Security in Nigeria critically examines the various data protection frameworks in Nigeria and how these are impacting curtailing cybercrimes in the country. The paper examined the institutions responsible for data security and how they carry it out. The work utilized both the secondary and primary sources of data collection. Key Informant Interview (KII) and the observation method were deployed to collect primary data for the study. Information on data protection was also collected from (NDPC) and other relevant agencies. Information from reports from the internet, scholarly articles in journals, and information from websites and books were used in the paper. The paper utilised the Social Strain Theory (SST) as the theoretical framework for the study. The paper observed that data protection regulations in Nigeria make it mandatory for all Public Institutions (PIs) in Nigeria to have a comprehensive cyber security framework, which is to protect against unauthorized access. Several factors are responsible for data insecurity and the attendant increase in cybercrimes in the country. These include, among others: i. Lack of knowledge on the part of most officers of the penalty for data breach allowed by them. ii. Poor dissemination of the content of the NDPA. iii. The poor economic condition of the country makes many officers to seek means of getting extra money, this also includes their volunteering information that they should not disclose in the first place. The paper observed that though cyber security in Nigeria is not within the mandate of the EFCC, the Commission plays very important role in dealing with the threat of cybercrimes in Nigeria. Records shows that of the 12,394 convictions of the EFCC from inception till 31st December 2023. Over 80% of them are on cybercrime and related offences. The paper concluded that inspire of the efforts of the EFCC and other agencies in tackling cybercrimes in Nigeria, the failure of the data protection frameworks in the country in ensuring confidentiality, integrity and security of the data at their disposal is the reason for the spiralling of cybercrimes in the country. The paper recommends that the Nigerian government adopt the best practice policies and regulations, promote awareness, and continuously update cyber security practices, which is germane to enhancing data protection in the country.

Strong reasons make strong actions: What Shakespeare’s ‘King John’ can teach us about the Internet of Things

The rapid proliferation of Internet of Things (IoT) devices in modern societies brings forth unprecedented opportunities for convenience and connectivity but also poses significant cyber security challenges. This paper examines the risks associated with these devices and the regulatory frameworks governing them in key regions including the US, the EU, China and India. Through a comprehensive analysis, it becomes evident that while efforts are being made to address IoT cyber security concerns, discrepancies in approaches and regulations hinder global harmonisation and create obstacles for industry compliance. Drawing from insights into existing cyber security frameworks and industry practices, the paper proposes actionable recommendations to enhance consumer IoT cyber security. These recommendations include defining baseline security requirements, promoting expertise within IoT workforces, advocating for the independent involvement of conformity assessment bodies (CABs), leveraging the quality infrastructure ecosystem, and launching an international awareness campaign. By implementing these measures, stakeholders can foster a safer and more secure IoT environment, mitigating the risks posed by cyber threats and ensuring the trust and resilience of connected devices. As society continues to navigate the complexities of IoT adoption, it is imperative to recognise the urgency of addressing cyber security challenges. By heeding the lessons from Shakespeare’s ‘King John’ — ‘Strong reasons make strong actions’ — and taking decisive steps to fortify IoT cyber security, we can safeguard individuals, businesses and critical infrastructure from the evolving threat landscape.

Integrating machine learning for sustaining cybersecurity in digital banks

Cybersecurity continues to be an important concern for financial institutions given the technology's rapid development and increasing adoption of digital services. Effective safety measures must be adopted to safeguard sensitive financial data and protect clients from potential harm due to the rise in cyber threats that target digital organizations. The aim of this study is to investigates how machine learning algorithms are integrated into cyber security measures in the context of digital banking and its benefits and drawbacks. We initially provide a general overview of digital banks and the particular security concerns that differentiate them from conventional banks. Then, we explore the value of machine learning in strengthening cybersecurity defenses. We revealed that insider threats, distributed denial of service (DDoS) assaults, ransomware, phishing attacks, and social engineering are main cyberthreats that are digital banks exposed. We identify the appropriate machine learning algorithms such as support vector machines (SVM), recurrent neural networks (RNN), hidden markov models (HMM), and local outlier factor (LOF) that are used for detection and prevention cyberthreats. In addition, we provide a model that considers ethical concerns while constructing a cybersecurity framework to address potential vulnerabilities in digital banking systems. The advantages and disadvantages of incorporating machine learning into the cybersecurity strategy of digital banks are outlined using strengths, weaknesses, opportunities, threats (SWOT) analysis. This study seeks to provide a thorough knowledge of how machine learning may strengthen cybersecurity procedures, protect digital banks, and maintain customer trust in the ecosystem of digital banking.