Advanced Intelligence-Based Risk Assessment for Preventing the Exploitation of Air Transportation in Criminal Activities

• In Event: Crime prevention, reoffending and organized crime

Abstract

Globalization has revolutionized the movement of goods and people, presenting both opportunities and challenges for border security. While facilitating trade and travel, this interconnectedness also amplifies the risk of illicit activities crossing borders undetected. Border Guards (BGs) and Law Enforcement Agencies (LEAs) play a pivotal role in screening passengers and goods to proactively identify potential threats. In this process, adopting a risk-based approach is essential to identifying high-risk passengers while minimizing human and economic costs for both authorities and economic actors. Although passenger data provides a rich source of information, effectively distinguishing passengers based on the risk they pose requires advanced intelligence-based profiling. Moreover, BGs and LEAs often lack the necessary technical skills and tools, and they may overlook the importance of coupling passengers' data with information about transnational crime patterns related to various forms of serious crime.
The Horizon Europe TENACITy Project addresses this critical gap by pioneering advanced intelligence-based risk assessment models. These models leverage passenger data alongside comprehensive insights into criminal actors, transportation methods, and common routes associated with illicit activities. By integrating state-of-the-art machine learning techniques, this study develops predictive models capable of assessing the risk associated with individual passengers, identifying behavioral patterns indicative of potential criminal involvement. This facilitates the development of precise risk profiles, enabling the early detection of high-risk individuals and enhancing travel intelligence practices.

Authors

• Sara Valle, Università Cattolica del Sacro Cuore – Transcrime

• Deborah Manzi, Università Cattolica del Sacro Cuore – Transcrime