A Novel Genetic Algorithm-Based Decisive Approach for Detection of Influencing Node in Terrorist Network (An Anti-Terrorism Approach)

In response to the destructiveness caused by terrorists, a framework for pinpointing pivotal nodes within their networks is necessary. This ‎study introduces a Genetic Algorithm-based framework, progressing through three phases to identify crucial nodes. The first phase filters ‎the network, the second employs the robust Genetic Algorithm to pinpoint critical nodes, and the third phase optimises for enhanced ‎accuracy. Empirical results demonstrate the framework's improvement over conventional centrality-based methods, showing enhancements ‎in concurrence, accuracy, and authenticity. The framework proposes a strategic shift toward focusing on the leaders of terrorist networks. ‎This strategic recalibration optimises law enforcement efforts, streamlining their interventions for maximum impact. The inherent potential of ‎this approach resonates in its capacity to significantly enhance the efficiency of security agencies. By concentrating resources on the nodes ‎that truly matter, a more targeted and impactful counter-terrorism strategy can be forged. This innovative framework thus holds the promise ‎of not only more effective counter-terrorism strategies but also a more adept response to the persistent challenges posed by terrorism‎.