Citation

Teh, Pin Shen and Teoh, Andrew Beng Jin and Ong, Thian Song and Neo, Han Foon (2007) Statistical Fusion Approach on Keystroke Dynamics. In: 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System, 16-18 Dec. 2007, Shanghai, China.

Text Statistical Fusion Approach on Keystroke Dynamics.pdf Restricted to Repository staff only Download (634kB)

Abstract

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)
Additional Information:	SITIS 2007: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SIGNAL IMAGE TECHNOLOGIES & INTERNET BASED SYSTEMS
Uncontrolled Keywords:	Feature extraction, Probability density function, Timing, Hidden Markov models
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 Information Science and Technology (FIST)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	29 Sep 2011 07:06
Last Modified:	21 Sep 2021 07:57
URII:	http://shdl.mmu.edu.my/id/eprint/2950

Downloads

Edit (login required)