Methods of OSINT and their integration with artificial intelligence technologies for strengthening information security

Abstract

Abstract. In the modern digital environment, the rapid growth of cyber threats has become one of themost pressing challenges for governments, organizations, and individuals. Cyberattacks are increasingly sophisticated, targeting critical infrastructures, private users, financial institutions, and the information space in general. Traditional security measures, such as signature-based detection systems or manual information analysis, are no longer enough to guarantee robust protection. So, integrating Open-Source Intelligence (OSINT) methods with artificial intelligence (AI) technologies has emerged as a highly effective approach to strengthening information security. OSINT in the Cybersecurity Context. OSINT refers to collecting and analyzing information from publicly available sources, such as websites, social media platforms, online databases, government reports, and technical registries. These techniques enable security professionals to obtain valuable insights into potential risks, threat actors, and vulnerabilities without compromising legal or ethical norms. However, the volume of data available in open sources is growing rapidly, which poses a serious challenge. Processing such information manually requires enormous time and human resources, increasing the probability of overlooking significant details. Aim and Relevance of the Research. This research aims to explore the possibilities of integrating OSINT tools with artificial intelligence algorithms to improve the efficiency of cybersecurity processes. This approach is highly relevant due to the growing demand for intelligent systems capable of collecting open-source data and classifying, organizing, and analyzing it in real time. These systems can offer early warning capabilities and strengthen proactive defense measures against cyber threats by minimizing human effort and errors.