Leveraging Guerrilla Intelligence Gathering Technique for Optimal Counterterrorism Operations: A Mathematical Perspective

Abstract

The research aims to explore the potential of leveraging guerrilla intelligence techniques for the optimization of counterterrorism (CT) operations, by taking a mathematical modeling approach. This study focuses on undermining the structural dynamics of a hierarchically structured terrorist organization consisting of three distinct classes of operatives: leaders, foot-soldiers, and recruiters. By developing a mathematical framework, this research seeks to provide insights into disrupting the operational capabilities and effectiveness of such organizations. The study began with analysis of the organization’s hierarchical structure, recognizes the critical roles played by each class of operatives in the evolution of terrorist activities. Leaders provide strategic guidance, foot-soldiers execute operations, and recruiters facilitate the expansion and replenishment of the organization's ranks. Understanding the interactions and dependencies among these classes is crucial for formulating effective CT strategies. Drawing inspiration from guerrilla intelligence gathering techniques, we formulated a system of differential equation model to capture the dynamics of the organization's structure. The model incorporates variables representing the population sizes of the three operatives’ class, as well as the rates of recruitment, promotion, commission, attrition, and defection. By considering these factors, the model aims to assess the impact of different strategies on the organization's viability and resilience. Furthermore, the research investigates the necessary and sufficient strategies for disrupting the organizational structure, - targeting at least two classes of operatives simultaneously. It also explores the effects of intelligence gathering, and the sabotaging effect of “syndromnized intelligence optimizing pseud-terrorist” (SIOP) agents. This allows for the evaluation of various scenarios and strategies, enabling the identification of optimal approaches to undermine the organization's structural dynamics. The study also recognizes the complex nature of terrorist organizations, including their adaptability and resilience. As such, we incorporated elements of organizational resilience evaluations. By considering the organization's response to CT efforts, the study aims to inform strategies that can effectively counteract potential recalcitrant operatives. The results of the analyses shows that the infiltration of at least 5% SIOP agents in a given “enemy-centric” CT environment has the potential to boost attrition accuracy by 60%, internal personnel defection (IPD) by 25%, vulnerability index by 81.71 %, and operational efficiency by 81.91%. Specifically, targeting all three classes of operatives simultaneously under this optimal CT option would yield 96.48% efficiency than other strategies. This level of interdiction is necessary and sufficient to optimally degrade a given organization to extinction within a period of 10 years, as well as inhibiting any propensity of sudden future strength resurgence. The targeting at least two classes of operative simultaneously was also highlighted and appraised empirically, to be necessary and sufficient for undermining the ingenious bureaucratic structure, high popularity and self-enforcing equilibrium that drive the resilience characteristics of most contemporary organizations. The outcomes of this study have significant implications for CT operations and policy formulation. By leveraging the insights gained from the model, decision-makers can develop targeted and evidence-based approaches to disrupt terrorists’ hierarchically structures. Ultimately, the findings from this study can contribute to enhancing the effectiveness of CT efforts, leading to improved security and stability in affected regions. In conclusion, this research proposes a mathematical model to explore the optimization of CT operations by leveraging guerrilla intelligence technique.