Robot Mimicry Attack on Keystroke-Dynamics User Identification and Authentication System

Yu, R., Kizilkaya, B. , Meng, Z., Li, E. , Zhao, G. and Imran, M. (2023) Robot Mimicry Attack on Keystroke-Dynamics User Identification and Authentication System. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), London, UK, 29 May - 02 Jun 2023, pp. 9879-9884. ISBN 9798350323658 (doi: 10.1109/ICRA48891.2023.10161423)

Abstract

Future robots will be very advanced with high flexibility and accurate control performance. They will have the ability to mimic human behaviours or even perform better, which raises the significant risk of robot attack. In this work, we study the robot mimic attack on the current keystroke-dynamic user authentication system. Specifically, we proposed a robot mimicry attack framework for keystroke-dynamics systems. We collected keyboard logging data and acoustical signal data from real users and extracted the timing pattern of keystrokes to understand victim's behaviour for robot imitation attacks. Furthermore, we develop a deep Q-Network (DQN) algorithm to control the velocity of robot which is one of the key challenges of forging the human typing timing features. We tested and evaluated our approach on the real-life robotic testbed. We presented our results considering user identification and user authentication performance. We achieved a 90.3% user identification accuracy with genuine keyboard logging data samples and 89.6% accuracy with robot-forged data samples. Furthermore, we achieved 11.1%, and 36.6% EER for user authentication performance with zero-effort attack, and robot mimicry attack, respectively.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zhao, Dr Guodong and Li, Dr Emma and Imran, Professor Muhammad and Meng, Zhen and KIZILKAYA, BURAK and Yu, Ms Rongyu
• Authors: Yu, R., Kizilkaya, B., Meng, Z., Li, E., Zhao, G., and Imran, M.
• College/School: College of Science and Engineering; College of Science and Engineering > School of Computing Science; College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• ISBN: 9798350323658
• Copyright Holders: Copyright © 2023 IEEE
• First Published: First published in 2023 IEEE International Conference on Robotics and Automation (ICRA)
• Publisher Policy: Reproduced in accordance with the publisher copyright policy