Password authentication is the most commonly used identification system in today's computer world. It can be enhanced using typing biometrics as a secondary check. Our research focuses on using the time period between keystrokes as the measure of the typing pattern. Each user's typing pattern can be viewed as a cluster of measurements that can be differentiated from clusters of other users. The effect of different metric spaces for cluster analysis was also investigated. The measurements of the keystroke latency are analysed using the modified K-means clustering algorithm to classify the users.
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