CEASEFIRE: An AI-powered system for combatting illicit firearms trafficking
Jorgen Cani, Ioannis Mademlis, Marina Mancuso, Caterina Paternoster, Emmanouil Adamakis, George Margetis, Sylvie Chambon, Alain Crouzil, Loubna Lechelek, Georgia Dede, Spyridon Evangelatos, George Lalas, Franck Mignet, Pantelis Linardatos, Konstantinos Kentrotis, Henryk Gierszal, Piotr Tyczka, Sophia Karagiorgou, George Pantelis, Georgios Stavropoulos, Konstantinos Votis, Georgios Th. Papadopoulos
TL;DR
The paper addresses the challenge of illicit firearms trafficking in the digital era, where cybercrime increasingly intertwines with offline trafficking. It proposes CEASEFIRE, an AI-powered system that integrates cyber-patrolling, offline and online trafficking analysis, information fusion, and cross-border data exchange to support law-enforcement workflows. The architecture blends multi-source data processing, advanced AI modules (e.g., CNN/Vision Transformer detectors, NLU, multilingual NLP, blockchain analytics) with interoperable interfaces to major information systems, enabling near-real-time intelligence and cross-jurisdiction collaboration. The work lays out five use-cases and a detailed technical stack, and discusses future directions such as predictive analytics, blockchain data integrity, and VR/AR training to enhance practical impact for LEAs.
Abstract
Modern technologies have led illicit firearms trafficking to partially merge with cybercrime, while simultaneously permitting its off-line aspects to become more sophisticated. Law enforcement officers face difficult challenges that require hi-tech solutions. This article presents a real-world system, powered by advanced Artificial Intelligence, for facilitating them in their everyday work.