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Your search keyword '"Tsai, Cheng-Jung"' showing total 35 results
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35 results on '"Tsai, Cheng-Jung"'

8. Reversible Fragile Watermarking for E-Learning Media

Author

Li, Yu-Chiang, Tsai, Cheng-Jung, Wu, Wei-Cheng, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Huang, Yueh-Min Ray, editor, Xu, Changsheng, editor, Cheng, Kuo-Sheng, editor, Yang, Jar-Ferr Kevin, editor, Swamy, M. N. S., editor, Li, Shipeng, editor, and Ding, Jen-Wen, editor

Published
2008
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9. An Evolutionary and Attribute-Oriented Ensemble Classifier

Author

Lee, Chien-I, Tsai, Cheng-Jung, Ku, Chih-Wei, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Gavrilova, Marina L., editor, Gervasi, Osvaldo, editor, Kumar, Vipin, editor, Tan, C. J. Kenneth, editor, Taniar, David, editor, Laganá, Antonio, editor, Mun, Youngsong, editor, and Choo, Hyunseung, editor

Published
2006
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28. A changeable personal identification number-based keystroke dynamics authentication system on smart phones.

Author

Chang, Ting-Yi, Tsai, Cheng-Jung, Tsai, Wang-Jui, Peng, Chun-Cheng, and Wu, Han-Sing

Subjects
PERSONAL identification numbers, KEYSTROKE timing authentication, SMARTPHONES, CELL phone security measures, ONLINE banking
Abstract

One can apply cell phones to access e-bank, buy stocks, pay credit card bills, and so on. The security issues of cell phones become extremely important. Most of subscribers use personal identification number (PIN) codes which combined with 6-8 numbers to protect their subscriber identity module cards from illegal accesses. It is easily to be decoded by the dictionary attack or shoulder surfing attack. Many studies employed keystroke dynamics to protect the PIN code, and the relative results exhibit that keystroke dynamics can indeed improve the security of a PIN code. However, the traditional keystroke dynamics-based authentication (KDA) system has to collect user's keystroke dynamics firstly and then produce a unique personal biometrics. It is inconvenient for users when changing their PIN codes is required, because the corresponding KDA systems should be retrained. To solve the previously mentioned drawbacks, this paper proposes a novel technique that allows users to change their PIN codes anytime without any extra retraining. This technique not only enhance the security of the PIN codes but also enrich the security of accessing e-bank, buying stocks, paying credit card bill, and other service via smart phones. Conducted experiment results show that the proposed system can effectively improve the KDA system to distinguish legitimate users and impostors even when users change their original passwords. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Published
2016
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35. An Evolutionary and Attribute-Oriented Ensemble Classifier.

Author

Gavrilova, Marina, Gervasi, Osvaldo, Kumar, Vipin, Tan, C. J. Kenneth, Taniar, David, Laganà, Antonio, Mun, Youngsong, Choo, Hyunseung, Lee, Chien-I, Tsai, Cheng-Jung, and Ku, Chih-Wei

Abstract

In the research area of decision tree, numerous researchers have been focusing on improving the predictive accuracy. However, obvious improvement can hardly be made until the introduction of the ensemble classifier. In this paper, we propose an Evolutionary Attribute-Oriented Ensemble Classifier (EAOEC) to improve the accuracy of sub-classifiers and at the same time maintain the diversity among them. EAOEC uses the idea of evolution to choose proper attribute subset for the building of every sub-classifier. To avoid the huge computation cost for the evolution, EAOEC uses the gini value gained during the construction of a sub-tree as the evolution basis to build the next sub-tree. Eventually, EAOEC classifier uses uniform weight voting to combine all sub-classifiers and experiments show that EAOEC can efficiently improve the predictive accuracy. [ABSTRACT FROM AUTHOR]

Published
2006
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