Performance enhancement on keystroke dynamics by using fusion rule


Teo, Andrew Beng Jin and Tee, Connie and Ong, Thian Song and Teh, Pin Shen (2008) Performance enhancement on keystroke dynamics by using fusion rule. Bahria University Journal of Information & Communication Technology (BUJICT), 1 (11). pp. 25-31. ISSN 1999‐4974

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Keystroke dynamics refers to the timing information that expresses precisely when each key was pressed and released as a person types. In this paper, we present a novel keystroke dynamic recognition system by using a novel fusion approach. Firstly, we extract four types of keystroke latency as the feature data from our dataset. We then calculate their mean and standard deviation to be stored as template. The test feature data will be transformed into similarity scores via Gaussian Probability Density Function (GPD). We also propose a new technique, known as Direction Similarity Measure (DSM), to measure the trend differential among each digraph in a phrase. Lastly, various fusion rules are applied to improve the final result by fusing the scores produced by GPD and DSM. Best result with equal error rate of 2.791% is obtained when the AND voting rule is used.

Item Type: Article
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 23 Jan 2014 03:47
Last Modified: 23 Jan 2014 03:47


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