On a user authentication method to realise an authentication system using s-EMG

Abstract

To prevent shoulder-surfing attacks, we proposed a user authentication method using surface electromyogram (s-EMG) signals, which can be used to identify who generated the signals and which gestures were made. Our method uses a technique called 'pass-gesture', which refers to a series of hand gestures, to achieve s-EMG-based authentication. However, it is necessary to introduce computer programs that can recognise gestures from the s-EMG signals. In this paper, we propose two methods that can be used to compare s-EMG signals and determine whether they were made by the same gesture. One uses support vector machines (SVMs), and the other uses dynamic time warping. We also introduced an appropriate method for selecting the validation data used to train SVMs using correlation coefficients and cross-correlation functions. A series of experiments was carried out to confirm the performance of those proposed methods, and the effectiveness of the two methods was confirmed.