Beeline - Cross-Network Identification of Users for Counter-Terrorism: Leveraging Open-Source Intelligence and Character Data Profiling

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This PhD research project aims to develop novel methods for identifying individuals engaged in potential terrorist activities across multiple online networks and platforms. The challenge lies in the fact that these individuals often use varying usernames and access points, complicating efforts to profile and track them. Building upon open-source intelligence (OSINT) techniques and character data profiling, this study will design innovative computational models to effectively profile and track a single individual across diverse networks. It will address the research gap in multi-source user identification, focusing on integrating disparate online behavioural patterns. The project will involve an extensive literature review, data collection, development and testing of algorithms, and validation of the model's effectiveness. The expected outcome is a robust framework that enhances counter-terrorism measures by improving the accuracy and efficiency of identifying potential threats in the digital sphere. This research holds significant implications for national security, law enforcement, and internet governance, ultimately contributing to safer online environments.