Methods of Extraction and Analysis of Intelligence to Combat Threats of Organized Crime at the Border

Abstract

The article reveals the development of innovative methods of intelligence-led policing in the form of information-analytical activity (IAA) by law enforcement operational units to combat threats of cross-border organized crime. The developed methodology for extracting intelligence information contains new procedures for extracting intelligence from Internet resources and performing intelligence analysis. It allowed for a reduction in time of 1.23 times for obtaining intelligence on criminal activity. Also, the methods for identifying crimes and analyzing threats to border security were improved. It allows the development of new procedures for crime identification, the classification of organized criminal groups, the formation of scenarios of their illegal activities, and the determination of the degree of their influence on border security. The methodology is based on taxonomy, artificial intelligence, expert evaluation, and SWOT analysis. The developed mathematical model for constructing operational cover at the border takes into account the dependence of the distribution of available resources on existing cross-border crime threats. Experimental verification of the implementation of the research results indicates advantages of the results in contrast to traditional approaches in terms of "reliability" and "efficiency". Based on the developed methodological apparatus, recommendations for improving the IAA were elaborated: improving processes of obtaining intelligence information; improving processes of identifying crimes and analyzing threats to border security due to the development of criminal analysis systems; creating regional centers for detecting and analyzing threats to border security; and developing the IAA based on enhancing the capabilities of operational units. Implementation of the scientific results into the practical activity of law enforcement operational units at the border contributed to increasing the efficiency of their IAA by up to 20%.