Despite their popularity, collaborative robots could be exploited in malicious attacks. The team investigated techniques that could identify a robot's actions by analyzing its network traffic. However, certain design choices could prevent leakage and make a system's network steadier. The research, On the Feasibility of Fingerprinting Collaborative Robot Network Traffic, was published in the proceedings of ARES 2025 and as part of the book series, Lecture Notes in Computer Science. More information: Cheng Tang et al, On the Feasibility of Fingerprinting Collaborative Robot Network Traffic, Lecture Notes in Computer Science (2025).