THINT: a Deep Learning Framework for Terrorist Threats Identification in Social Media

This paper presents THINT (THreat INTelligence Framework), a novel framework leveraging deep learning for the Open-Source Intelligence (OSINT) analysis of social media to identify terrorist related threats. Criminal organizations and terrorist groups are continually exploiting social media for radicalization campaigns and various illegal activities. The THINT framework addresses this emerging threat landscape by harnessing advanced deep learning algorithms, enhancing the early detection capability of terrorism-related content. Through meticulous fine-tuning during the training phase, THINT significantly outperforms previous models, offering enhanced identification and classification of threats. Compared to traditional Machine Learning (ML) approaches, such as Support Vector Machines (SVM), our framework not only demonstrates superior accuracy but also reduces classification time. These improvements represent a meaningful innovation in the usage of OSINT investigations to fight against terrorism and organised crime.