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.
倪桂强，李佳桢，潘志松，缪志敏. 基于支持向量数据描述的击键生物特征认证*[J]. 模式识别与人工智能, 2008, 21(5): 704-708.
NI Gui-Qiang, LI Jia-Zhen, PAN Zhi-Song, MIAO Zhi-Min. Verification Based on Keystroke Biologic Characteristics Using Support Vector Data Description. , 2008, 21(5): 704-708.
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2008, Vol. 21 
