Survey on a New Model for Predicting and Dismantling a Complex Terrorist Network

Terrorist attacks keep happening around the world, which has led researchers to use Social Network Analysis (SNA) as a way to study terrorism. Terrorist groups function like secretive networks, strengthening their operations while staying hidden. This study introduces a new approach to reveal and break apart such networks by using four different centrality measures. First, the method predict hidden or missing link in the network using these centrality measures. Then, the network is dismantled by applying the Galton-Watson extinction probability model, which helps estimate the chances of the network collapsing. The study looks at real-world cases, such as the 9/11 terrorist attacks and the M-19 group, to test how well link prediction works. It shows that removing the most influential members (highly ranked nodes) is essential for weakening and destroying a terrorist network. Additionally, the research examines how dangerous the network is (lethality) and how tightly connected its members are (bonding), since cohesiveness is critical for a network’s survival. The results demonstrate that link prediction is a key tool for exposing hidden terrorist networks, making it an important strategy for counterterrorism efforts.