论文信息 - User Authentication based on Human Typing Pattern with Artificial Neural Networks and Support Vector Machine

User Authentication based on Human Typing Pattern with Artificial Neural Networks and Support Vector Machine

As an attempt to develop a more powerful authentication system, with low cost and good acceptance by users, we proposed here an authentication mechanism based on biometric information of human typing pattern. At the moment, we present a complete description of the architecture with multi pattern verification units and results of a first phase implementation of the mechanism based on a single pattern verification unit among Multi Layer Perceptron, Learning Vector-Quantization, Self-Organizing Neural Networks and Support vector machine.

[1] B. Hussien,et al. Computer-Access Security Systems Using Keystroke Dynamics , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[2] Michael Wagner,et al. Keyboard user verification: toward an accurate, efficient, and ecologically valid algorithm , 1995, Int. J. Hum. Comput. Stud..

[3] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[4] Vladimir Vapnik,et al. The Nature of Statistical Learning , 1995 .

[5] Sharath Pankanti,et al. Biometrics: Future of Identification , 2000 .

[6] Nello Cristianini,et al. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[7] Mohammad S. Obaidat,et al. Verification of computer users using keystroke dynamics , 1997, IEEE Trans. Syst. Man Cybern. Part B.

[8] William Stallings,et al. Cryptography and Network Security: Principles and Practice , 1998 .

[9] Daw-Tung Lin. Computer-access authentication with neural network based keystroke identity verification , 1997, Proceedings of International Conference on Neural Networks (ICNN'97).