Analysis and Forecasting of Vulnerabilities with AI for Decision Support
In this article, we address questions, such as: How to structure, analyze, and forecast the development of vulnerabilities in the constantly changing world around us? What threat landscape have we experienced in the past, and which attack vectors are most important at the moment?How to adapt to the coming cyberspace threats?We aim to help politicians, decision-makers, industry, lawyers, and technological pioneers adapt their defenses when the rules of the game are constantly evolving.Protecting organizations against the increasing number of cyber-attacks has become as crucial as it is complicated.To be effective in identifying and defeating such attacks, cyber analysts require novel threat modelling methodologies based on AI techniques that can automatically recommend protection measures for current and future periods.We propose a custom, simple, explainable on-site approach to recommend the most significant threats.Our goal is to provide a solution that could extract vulnerability features from the CVE database, find related correlations in a fast and scalable way, and automate recommendations, reducing the number of manual research activities and increasing the organization's security.
Authors
- Roman Graf (ORCID: https://orcid.org/0000-0002-4479-2092)
- Artūrs Lavrenovs (ORCID: https://orcid.org/0000-0001-9961-2637)
Publication Details
- Published
- 2025-09-21
- DOI
- https://doi.org/10.51408/csit2025_36
- Primary Topic
- Anomaly Detection Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00