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arXiv · 2506.14116

Haptic-Based User Authentication for Tele-robotic System

Rongyu Yu·Kan Chen·Zeyu Deng·Chen Wang·Burak Kizilkaya·Liying Emma Li
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Abstract

Tele-operated robots rely on real-time user behavior mapping for remote tasks, but ensuring secure authentication remains a challenge. Traditional methods, such as passwords and static biometrics, are vulnerable to spoofing and replay attacks, particularly in high-stakes, continuous interactions. This paper presents a novel anti-spoofing and anti-replay authentication approach that leverages distinctive user behavioral features extracted from haptic feedback during human-robot interactions. To evaluate our authentication approach, we collected a time-series force feedback dataset from 15 participants performing seven distinct tasks. We then developed a transformer-based deep learning model to extract temporal features from the haptic signals. By analyzing user-specific force dynamics, our method achieves over 90 percent accuracy in both user identification and task classification, demonstrating its potential for enhancing access control and identity assurance in tele-robotic systems.

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Rongyu Yu, Kan Chen, Zeyu Deng, Chen Wang, Burak Kizilkaya, Liying Emma Li. 2025-06-17. Haptic-Based User Authentication for Tele-robotic System. https://arxiv.org/abs/2506.14116

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