Robot Behavior-Based User Authentication for Motion-Controlled Robotic Systems

Huang, L., Meng, Z., Deng, Z., Wang, C., Li, L. and Zhao, G. (2021) Robot Behavior-Based User Authentication for Motion-Controlled Robotic Systems. In: WiSARN 2021: International Workshop on Wireless Sensor, Robot and UAV Networks, 10 May 2021, ISBN 9781665447140 (doi: 10.1109/INFOCOMWKSHPS51825.2021.9484589)

Abstract

Motion-controlled robotic systems would become more and more popular in the future since they allow humans to easily control robots to carry out various tasks. However, current authentication methods rely on static credentials, such as passwords, fingerprints, and faces, which are independent of the robot control. Thus, they cannot guarantee that a robot is always under the control of its enrolled user. In this paper, we build a motion-controlled robotic arm system and show that a robotic arm’s motion inherits much of its user’s behavioral information in interactive control scenarios. Based on that, we propose a novel user authentication approach to verify the robotic arm user. In particular, we log the angle readings of the robotic arm’s joints to reconstruct the 3D movement trajectory of its end effector. We then develop a learning-based algorithm to identify the user. Extensive experiments show that our system achieves 95% accuracy to verify users while preventing various impersonation attacks.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Meng, Mr Zhen and Li, Dr Emma and Zhao, Dr Guodong
• Authors: Huang, L., Meng, Z., Deng, Z., Wang, C., Li, L., and Zhao, G.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• ISBN: 9781665447140
• Copyright Holders: Copyright © 2021 IEEE
• First Published: First published in Proceedings of IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher

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