Statistical Fusion Approach on Keystroke Dynamics


Pin Shen, Teh and Andrew Beng Jin, Teoh and Thian Song, Ong and Han Foon, Neo (2007) Statistical Fusion Approach on Keystroke Dynamics. In: IEEE International Conference on Signal Image Technology and Internet Based Systems, 16-19 DEC 2007, Shanghai, PEOPLES R CHINA.

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Keystroke dynamics refers to a user's habitual typing characteristics. These typing characteristics are believed to be unique among large populations. In this paper, we present a novel keystroke dynamic recognition system by using a fusion method. Firstly, we record the dwell time and the flight time as the feature data. We then calculate their mean and standard deviation values and stored The test feature data will be transformed into the scores via Gaussian probability density function. On the other hand, we also propose a new technique, known as Direction Similarity Measure (DSM) to measure the differential of sign among each coupled characters in a phrase. Lastly, a weighted sum rule is applied by fusing the Gaussian scores and the DSM to enhance the final result. The best result of equal error rate 6.36% is obtained by using our home-made dataset.

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > T Technology (General)
Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 29 Sep 2011 07:06
Last Modified: 29 Sep 2011 07:06


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