Vision Paper: Addressing the Threat of 3D Printing Firearm Files with Data-Driven Strategies

Vision Paper: Addressing the Threat of 3D Printing Firearm Files with Data-Driven Strategies

연구 분야: Strategies

학회: 2024 IEEE International Conference on Big Data (BigData)

With the introduction of 3D printing technology, manufacturing has undergone a revolutionary change, offering unprecedented access to custom object production. However, this democratization has also led to significant public safety concerns, particularly regarding the creation and distribution of 3D-printed firearms. This paper outlines a vision for a comprehensive framework to monitor and analyze the lifecycle of 3D firearm models, employing advanced tools such as web crawling, Natural Language Understanding (NLU), 3D file analysis, and image classification. The framework aims to track the distribution of 3D files across online platforms, analyze the contents of 3D files to identify firearm components, and detect 3D-printed firearms in images. By leveraging these technologies, law enforcement agencies (LEAs) can gain actionable insights for reducing the risks posed by illicit 3D printing activities.