arXiv subjects

Martijn Dekker

Publications and source records attributed to Martijn Dekker.

3 recordsLinked to original sources

arXiv2026

Uncertainty in security: managing cyber senescence

My main worry, and the core of my research, is that our cybersecurity ecosystem is slowly but surely aging and getting old and that aging is becoming an operational risk. This is happening not only because of growing complexity, but more importantly because of accumulation of controls and measures whose effectiveness are uncertain. I introduce a new term for this aging phenomenon: cyber senescence. I will begin my lecture with a short historical overview in which I sketch a development over time that led to this worry for the future of cybersecurity. It is this worry that determined my research agenda and its central theme of the role of uncertainty in cybersecurity. My worry is that waste is accumulating in cyberspace. This waste consists of a multitude of overlapping controls whose risk reductions are uncertain. Unless we start pruning these control frameworks, this waste accumulation causes aging of cyberspace and could ultimately lead to a system collapse.

cs.CR↗

arXiv2024

Towards an AI-Enhanced Cyber Threat Intelligence Processing Pipeline

Cyber threats continue to evolve in complexity, thereby traditional Cyber Threat Intelligence (CTI) methods struggle to keep pace. AI offers a potential solution, automating and enhancing various tasks, from data ingestion to resilience verification. This paper explores the potential of integrating Artificial Intelligence (AI) into CTI. We provide a blueprint of an AI-enhanced CTI processing pipeline, and detail its components and functionalities. The pipeline highlights the collaboration of AI and human expertise, which is necessary to produce timely and high-fidelity cyber threat intelligence. We also explore the automated generation of mitigation recommendations, harnessing AI's capabilities to provide real-time, contextual, and predictive insights. However, the integration of AI into CTI is not without challenges. Thereby, we discuss ethical dilemmas, potential biases, and the imperative for transparency in AI-driven decisions. We address the need for data privacy, consent mechanisms, and the potential misuse of technology. Moreover, we highlights the importance of addressing biases both during CTI analysis and AI models warranting their transparency and interpretability. Lastly, our work points out future research directions such as the exploration of advanced AI models to augment cyber defences, and the human-AI collaboration optimization. Ultimately, the fusion of AI with CTI appears to hold significant potential in cybersecurity domain.

cs.CR↗

arXiv2023

A Threat-Intelligence Driven Methodology to Incorporate Uncertainty in Cyber Risk Analysis and Enhance Decision Making

The challenge of decision-making under uncertainty in information security has become increasingly important, given the unpredictable probabilities and effects of events in the ever-changing cyber threat landscape. Cyber threat intelligence provides decision-makers with the necessary information and context to understand and anticipate potential threats, reducing uncertainty and improving the accuracy of risk analysis. The latter is a principal element of evidence-based decision-making, and it is essential to recognize that addressing uncertainty requires a new, threat-intelligence driven methodology and risk analysis approach. We propose a solution to this challenge by introducing a threat-intelligence based security assessment methodology and a decision-making strategy that considers both known unknowns and unknown unknowns. The proposed methodology aims to enhance the quality of decision-making by utilizing causal graphs, which offer an alternative to conventional methodologies that rely on attack trees, resulting in a reduction of uncertainty. Furthermore, we consider tactics, techniques, and procedures that are possible, probable, and plausible, improving the predictability of adversary behavior. Our proposed solution provides practical guidance for information security leaders to make informed decisions in uncertain situations. This paper offers a new perspective on addressing the challenge of decision-making under uncertainty in information security by introducing a methodology that can help decision-makers navigate the intricacies of the dynamic and continuously evolving landscape of cyber threats.

cs.CR↗