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

  • Authors

    • Saurabh Singh Jabalpur Engineering College, Jabalpur, Madhya Pradesh, 482001, India
    • Madhuri Gokhale Jabalpur Engineering College, Jabalpur, Madhya Pradesh, 482001, India
    • Om Prakash Chauhan Jabalpur Engineering College, Jabalpur, Madhya Pradesh, 482001, India
    • Dr. Kanchan Cecil Jabalpur Engineering College, Jabalpur, Madhya Pradesh, 482001, India
    • Dr. S. K. Mahobiya Jabalpur Engineering College, Jabalpur, Madhya Pradesh, 482001, India
    • Namarta Sahayam Jabalpur Engineering College, Jabalpur, Madhya Pradesh, 482001, India
    • Khushi Koshta Jabalpur Engineering College, Jabalpur, Madhya Pradesh, 482001, India
    • Abhay Bairagi Jabalpur Engineering College, Jabalpur, Madhya Pradesh, 482001, India
    • D. M. Balaji Jabalpur Engineering College, Jabalpur, Madhya Pradesh, 482001, India
    • Preshit Tiwari Jabalpur Engineering College, Jabalpur, Madhya Pradesh, 482001, India
    • Dr. Mahesh Motwani Rajiv Gandhi Prodhyogiki Vishwavidyalaya, Bhopal, Madhya Pradesh, 462033 India
    • Dr. Anu Sayal School of Accounting and Finance, Taylor's University. Subang Jaya, 47500, MALAYSIA
    https://doi.org/10.14419/xgbrcc61

    Received date: April 16, 2025

    Accepted date: June 10, 2025

    Published date: June 18, 2025

  • Betweenness Centrality Measure (BT); Closeness Centrality (CL); Degree Centrality (D); Page Rank Measure (PR); Terrorist Network (Tn)‎.

  • Abstract

    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.

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  • How to Cite

    Singh , S. ., Gokhale , M. ., Chauhan , O. P. ., Cecil, D. K. . ., Mahobiya , D. S. K. ., Sahayam , N. ., Koshta , K. ., Bairagi , A. ., Balaji , D. M. ., Tiwari , P. ., Motwani , D. M. ., & Sayal , D. A. . (2025). A Novel Genetic Algorithm-Based Decisive Approach for Detection of Influencing Node in Terrorist ‎Network (An Anti-Terrorism Approach)‎. International Journal of Basic and Applied Sciences, 14(2), 247-259. https://doi.org/10.14419/xgbrcc61