Novelty Detection Approach for Keystroke Dynamics Identity Verification-Reference-Cited by-同舟云学术

Novelty Detection Approach for Keystroke Dynamics Identity Verification

Published:2003 Issue: Volume: Page:1016-1023
ISSN:0302-9743
Container-title:Intelligent Data Engineering and Automated Learning
language:
Short-container-title:

Author:

Yu Enzhe,Cho Sungzoon

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-45080-1_143

Reference10 articles.

1. Cho, S., Han, C., Han, D., Kim, H.: Web-based keystroke dynamics identity verification using neural network. Journal of organizational computing and electronic commerce 10(4), 295–307 (2000)

2. Gaines, R., Lisowski, W., Press, S., Shapiro, N.: Authentication by keystroke timing: some preliminary results. Rand Report R-256-NSF. Rand Corporation (1980)

3. Hwang, B., Cho, S.: Characteristic of Autoassociative MLP as a Novelty Detector. In: International Joint Conference on Neural Networks, Washington DC USA (July 1999)

4. Ikbal, M., Misra, H., Yegnanarayana, B.: Analysis of sutoassociative mapping neural networks, In: Proceedings of International Joint Conference on Neural Networks, #854 (1999)

5. Kramer, M.: Nonlinear principal component analysis using autoassociative neural networks. AIChE Journal 37(2) (February 1991)

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