Since computer users are different at degrees of familiarity with keyboards and keystroke habits, each user has his particular keystroke characteristics. To one user, his keystroke characteristics are normal classes, and all the other users' are abnormal. Thus this problem can be resolved by one-class classifier. The keystroke verification based on support vector data description (SVDD) is proposed. Through experiments, SVDD is compared with BP, RBF and SOM, and the results show SVDD has better performance. It decreases impostor pass rate (IPR) from 28.9% to 0.28%. Finally, an password & keystroke characteristics identity verification system is presented.
NI Gui-Qiang,LI Jia-Zhen,PAN Zhi-Song等. Verification Based on Keystroke Biologic Characteristics Using Support Vector Data Description[J]. , 2008, 21(5): 704-708.
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2008, Vol. 21 
