Threshold selection for keystroke dynamics identification system

Keystroke dynamics is the timing information captured when typing on a computer keyboard. It includes hold time and inter-key time. In authentication and identification systems, a threshold is an essential element used in the decision-making process to determine whether a user be granted access or not. Therefore, the threshold selection process is vital. In this work, 15 users were asked to type long texts using a word processor twice a day for 10 days. Two scenarios were used to determine the ability to identify users. EER and accuracy were used to confirm the result and find the most appropriate threshold. The result showed that the highest count thresholds were 0.20 and 0.30. When confirmed by using EER and accuracy, the optimal threshold is 0.20 with an EER of 0.08% and an accuracy of 87.60%. Additionally, our proposed method outperforms those that use free texts to create typing patterns.