P069. Leveraging Forensic Intelligence to Disrupt Criminal Networks

• In Event: Poster Session & Ice Cream Social

Abstract

This study examines the added value of forensic intelligence (FI) in uncovering hidden actors and vulnerabilities within resilient criminal networks. By integrating FI data into network analysis, this research explores how FI enhances the identification of covert connections and weak points. Networks are simulated using Barabási-Albert methods and small-world structures. The study evaluates network resilience through key metrics, including the largest connected component, density, average shortest path length, clustering coefficient, betweenness centrality, and eigenvector centrality, providing a comprehensive assessment of structural vulnerabilities and the impact of forensic intelligence on network disruption. Disruption scenarios tested include key player removal, financial disruption, communication targeting, closeness targeting, betweenness targeting, degree targeting, and random disruptions. Research expects to suggest that FI improves law enforcement’s ability to disrupt covert networks by exposing hidden actors and increasing the effectiveness of targeted interventions. This research is aimed at establishing a framework for integrating forensic intelligence into criminal network disruption strategies, offering new insights for law enforcement agencies combating crime.

Authors

• Dayle Harvey, Ghent University

• Kuralarasan Kumar, Univesity of Ghent

• Christophe Vandeviver, Ghent University

• Ruslan Klymentiev, Ghent University