An Aggregated Information Technology Checklist for Operational Risk Management

This study addresses the issue of the Information Technology (IT) Governance frameworks and standards that respond to different levels of operational risks, especially those caused by the information systems and technology infrastructure. A requirement analysis regarding Basel II is conducted, a gap analysis between the Information Control Models (ICMs) is performed, and the aggregated IT checklist for Operational Risk Management (ORM) is proposed by mapping the control objectives in ICMs to the operational risk categories described in Basel II as loss event types. The validity and reliability of the study is based on the focus group assessment of the mappingsBasel II, Operational Risk Management, Information Control Model, Information Technology Governance.

Understanding Malicious Attacks Against Infrastructures - Overview on the Assessment and Management of Threats and Attacks to Industrial Control Systems

This report describes approaches to the assessment and management of malicious threats and attacks relating to critical infrastructures in general, and electric power infrastructures in particular. Securing infrastructures implies taking into account both the natural and man-made (intentional) events. While protecting against the natural disruptive events is a feasible (yet not trivial) task, benefiting by well-established practices, dealing with intentional attacks comes up across many difficulties, especially due to the unpredictability of such events. The report outlines the state-of-the-art in dealing with threats and malicious attacks, considering both physical and cyber actions. Several approaches taken at national and international levels towards securing the critical infrastructures are also provided.JRC.G.6-Sensors, radar technologies and cybersecurit

National Security and Cyber Defense in the Rise of Artificial Super Intelligence

The rapid advancements in Artificial Intelligence (AI) have significantly altered the global cyber security landscape, marking the emergence of Artificial superintelligence (ASI) as a transformative force in digital warfare. Unlike Artificial General Intelligence (AGI), characterized by human equivalent cognitive functions, ASI represents a level of intelligence vastly exceeding human capacities, capable of autonomous reasoning, real-time threat analysis, and adaptive decision-making. The role of ASI in cybersecurity is paradoxical, embodying both extraordinary defensive potential and unprecedented offensive risks. On the defensive side, ASI empowers cyber security frameworks with real-time predictive analytics, automated threat detection, and rapid incident response, significantly improving national security preparedness. Conversely, the offensive exploitation of ASI capabilities introduces severe threats, including sophisticated cyber-attacks, advanced misinformation campaigns, autonomous malware proliferation, and algorithmic manipulation. Moreover, ASI’s vulnerability to adversarial manipulation through data poisoning and adversarial machine learning poses additional, substantial risks to national and individual privacy. The complexity inherent in ASI systems, particularly their opaque decision-making processes (the “black box” problem), further compounds ethical and practical challenges, emphasizing the need for rigorous oversight and transparent frameworks. This paper explores the dual nature of ASI, presenting in-depth analyses of real-world scenarios of AI-driven cyberattacks alongside advanced countermeasures and policy recommendations. Key strategies discussed include AI-driven deception techniques, blockchain integration, zero-trust cybersecurity models, and comprehensive international regulatory frameworks. The objective is to provide a structured pathway for policymakers, security professionals, and researchers, ensuring that ASI serves as a compelling national security asset rather than becoming a catalyst for intensified cyber warfare

National Security and Cyber Defense in the Rise of Artificial Super Intelligence

The rapid advancements in Artificial Intelligence (AI) have significantly altered the global cyber security landscape, marking the emergence of Artificial superintelligence (ASI) as a transformative force in digital warfare. Unlike Artificial General Intelligence (AGI), characterized by human equivalent cognitive functions, ASI represents a level of intelligence vastly exceeding human capacities, capable of autonomous reasoning, real-time threat analysis, and adaptive decision-making. The role of ASI in cybersecurity is paradoxical, embodying both extraordinary defensive potential and unprecedented offensive risks. On the defensive side, ASI empowers cyber security frameworks with real-time predictive analytics, automated threat detection, and rapid incident response, significantly improving national security preparedness. Conversely, the offensive exploitation of ASI capabilities introduces severe threats, including sophisticated cyber-attacks, advanced misinformation campaigns, autonomous malware proliferation, and algorithmic manipulation. Moreover, ASI’s vulnerability to adversarial manipulation through data poisoning and adversarial machine learning poses additional, substantial risks to national and individual privacy. The complexity inherent in ASI systems, particularly their opaque decision-making processes (the “black box” problem), further compounds ethical and practical challenges, emphasizing the need for rigorous oversight and transparent frameworks. This paper explores the dual nature of ASI, presenting in-depth analyses of real-world scenarios of AI-driven cyberattacks alongside advanced countermeasures and policy recommendations. Key strategies discussed include AI-driven deception techniques, blockchain integration, zero-trust cybersecurity models, and comprehensive international regulatory frameworks. The objective is to provide a structured pathway for policymakers, security professionals, and researchers, ensuring that ASI serves as a compelling national security asset rather than becoming a catalyst for intensified cyber warfare

Cyber Threat Landscape Analysis for Starlink Assessing Risks and Mitigation Strategies in the Global Satellite Internet Infrastructure

Satellite internet networks have emerged as indispensable components of the modern digital landscape, promising to extend connectivity to even the most remote corners of the globe. Among these networks, Starlink, pioneered by SpaceX, has garnered significant attention for its ambitious mission to provide high-speed internet access on a global scale. However, the proliferation of satellite infrastructure also brings to the forefront a myriad of cybersecurity challenges, as these networks become increasingly vital for critical communication and data exchange. This research endeavours to conduct a comprehensive analysis of the cybersecurity landscape surrounding Starlink, with a focus on identifying potential threats, assessing associated risks, and proposing mitigation strategies to bolster the resilience of the network. Through an exploration of existing literature, an examination of the system architecture of Starlink, and an analysis of the current cyber threat landscape facing satellite internet networks, this study aims to provide valuable insights into the cybersecurity challenges inherent in the operation of global satellite internet infrastructure. By prioritizing risks and proposing effective mitigation strategies, this research seeks to contribute to the ongoing efforts to safeguard the integrity and accessibility of satellite-based internet connectivity.Comment: 25 Page

Artificial Intelligence: Making crime easier in the world of finance?

Purpose – This paper explores the dual role of artificial intelligence (AI) in the realm of finance, examining its potential to both enhance efficiency and exacerbate vulnerabilities to criminal activitiesMethod – The research methodology for this study focuses on exploring the relationship between artificial intelligence (AI) and its potential role in facilitating financial crimes. This section outlines the research design, data collection methods, data analysis techniques, and ethical considerationsResult – As AI technologies become increasingly integrated into financial systems, they offer unprecedented opportunities for streamlining operations, optimizing decision-making processes, and enhancing customer experiences. However, this digital transformation also presents new challenges, particularly in terms of security and fraud preventionImplication – By leveraging advanced algorithms and machine learning techniques, malicious actors may exploit AI-powered systems to perpetrate financial crimes with greater sophistication and scaleOriginality – This paper evaluates the implications of this evolving landscape, highlighting the need for robust regulatory frameworks, proactive risk management strategies, and ongoing collaboration between industry stakeholders and law enforcement agencies to mitigate the risks associated with AI-enabled financial crim

A Survey of Interdependent Information Security Games

Risks faced by information system operators and users are not only determined by their own security posture, but are also heavily affected by the security-related decisions of others. This interdependence between information system operators and users is a fundamental property that shapes the efficiency of security defense solutions. Game theory is the most appropriate method to model the strategic interactions between these participants. In this survey, we summarize game-theoretic interdependence models, characterize the emerging security inefficiencies, and present mechanisms to improve the security decisions of the participants. We focus our attention on games with interdependent defenders and do not discuss two-player attackerdefender games. Our goal is to distill the main insights from the state-of-the-art and to identify the areas that need more attention from the research community