Additive manufacturing (AM) or 3D printing is an emerging manufacturing technology that plays a growing role in both industrial and consumer settings. However, security concerns of AM systems have been raised among researchers. In this paper, we present an online detection mechanism for the malicious attempts on AM systems, which taps into both audio and video signals collected during the printing process. For audio signals, we propose to monitor the shift of patterns in the spectrogram and dominant frequencies via a control chart designed based on the Wasserstein metric. For video signals, we propose to monitor the change in the reconstructed path of the extruder via a Hausdorff metric. We then show the effectiveness of our methods in a case study using an Ender 3D printer, where the cyber-incidence of altering the internal fill density can be easily identified in an online manner.

中文翻译：

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通过分析多媒体信号在线检测增材制造系统中的网络事件

增材制造 (AM) 或 3D 打印是一种新兴的制造技术，在工业和消费环境中发挥着越来越重要的作用。然而，研究人员已经提出了 AM 系统的安全问题。在本文中，我们提出了一种针对 AM 系统恶意尝试的在线检测机制，该机制利用在打印过程中收集的音频和视频信号。对于音频信号，我们建议通过基于 Wasserstein 度量设计的控制图来监控频谱图中模式的变化和主要频率。对于视频信号，我们建议通过 Hausdorff 度量来监控挤出机重建路径的变化。然后，我们在使用 Ender 3D 打印机的案例研究中展示了我们方法的有效性，