Database and Benchmark for Early-stage Malicious Activity Detection in 3D Printing

Xiaolong Ma
Xiaolong Ma
Hongjia Li
Hongjia Li
Qiyuan An
Qiyuan An

ASP-DAC, pp. 494-499, 2020.

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Abstract:

Increasing malicious users have sought practices to leverage 3D printing technology to produce unlawful tools in criminal activities. It is of vital importance to enable 3D printers to identify the objects to be printed and terminate at early stage if illegal objects are identified. Deep learning yields significant rises in performance in...More

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