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Article type: Research Article
Authors: Mishra, Amit Kumara; * | Bhardwaj, Ramakantb; * | Joshi, Nisheethc | Mathur, Itic
Affiliations: [a] Department of Computer Science and Engineering, Amity School of Engineering and Technology (ASET), Amity University, Madhya Pradesh, India | [b] Department of Mathematics, Amity University, Kolkata, WB, India | [c] Department of Computer Science and Engineering, Banasthali Vidyapeeth, Tonk, Rajasthan, India
Correspondence: [*] Corresponding authors. Dr. Amit Kumar Mishra, Department of Computer Science and Engineering, Amity School of Engineering and Technology (ASET), Amity University, Gwalior (MP) – 474005, India. E-mail: [email protected]; Ramakant Bhardwaj, Department of Mathematics, Amity University, Kolkata-700135, WB, India. E-mail: [email protected].
Abstract: This paper aims to select the appropriate node(s) to effectively destabilize the terrorist network in order to reduce the terrorist group’s effectiveness. Considerations are introduced in this literature as fuzzy soft sets. Using the weighted average combination rule and the D–S theory of evidence, we created an algorithm to determine which node(s) should be isolated from the network in order to destabilize the terrorist network. The paper may also prove that if its power and foot soldiers simultaneously decrease, terrorist groups will collapse. This paper also proposes using entropy-based centrality, vote rank centrality, and resilience centrality to neutralize the network effectively. The terrorist network considered for this study is a network of the 26/11 Mumbai attack created by Sarita Azad.
Keywords: Terrorist network mining (TNM), destabilization, centralities, fuzzy soft set, social network analysis (SNA), global network efficiency, average clustering coefficient, Dempster–Shafer theory of evidence
DOI: 10.3233/JIFS-210425
Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 35-48, 2022
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