Trojan Attacks on Neural Network Controllers for Robotic Systems
Industry
Source: arXiv cs.ROPublish time unverified
arXiv:2602.05121v3 Announce Type: replace-cross Abstract: Neural network controllers are increasingly deployed in robotic systems for tasks such as trajectory tracking and pose stabilization. However, their reliance on potentially untrusted training pipelines or supply chains introduces significant security vulnerabilities. This paper investigates backdoor (Trojan) attacks against neural controllers, using a differential-drive mobile robot platform as a case study.