Studie možností zpravodajství z otevřených zdrojů v oblasti kriminality

Abstract

This thesis focuses on the systematic analysis of methods for collecting, processing, and utilizing information from open sources (OSINT) in the context of security practices. The aim of the thesis was to critically evaluate methodological approaches to efficient data collection, validation, and analytical processing with an emphasis on applications in cybersecurity and criminal intelligence. The work combines theoretical insights with practical applications through case studies that include uncovering phishing campaigns, identifying perpetrators of organized crime, and simulating a penetration test targeting students' vulnerability to cyber threats. Special emphasis is placed on the dynamic nature of OSINT data, which changes daily and requires continuous updates and adaptation of analytical methods. The results confirm that OSINT is an effective tool for both security forces and the private sector, with its importance steadily growing in the digitally interconnected world.