Cost-Effective Kernel Ridge Regression Implementation for Keystroke-Based Active Authentication System
In this paper, a fast kernel ridge regression (KRR) learning algorithm is adopted with O(N) training cost for largescale active authentication system. A truncated Gaussian radial basis function (TRBF) kernel is also implemented to provide better cost-performance tradeoff. The fast-KRR algorithm alon...
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| Published in | IEEE transactions on cybernetics Vol. 47; no. 11; pp. 3916 - 3927 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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United States
IEEE
01.11.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| Abstract | In this paper, a fast kernel ridge regression (KRR) learning algorithm is adopted with O(N) training cost for largescale active authentication system. A truncated Gaussian radial basis function (TRBF) kernel is also implemented to provide better cost-performance tradeoff. The fast-KRR algorithm along with the TRBF kernel offers computational advantages over the traditional support vector machine (SVM) with Gaussian-RBF kernel while preserving the error rate performance. Experimental results validate the cost-effectiveness of the developed authentication system. In numbers, the fast-KRR learning model achieves an equal error rate (EER) of 1.39% with O(N) training time, while SVM with the RBF kernel shows an EER of 1.41% with O(N 2 ) training time. |
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| AbstractList | In this paper, a fast kernel ridge regression (KRR) learning algorithm is adopted with O(N) training cost for largescale active authentication system. A truncated Gaussian radial basis function (TRBF) kernel is also implemented to provide better cost-performance tradeoff. The fast-KRR algorithm along with the TRBF kernel offers computational advantages over the traditional support vector machine (SVM) with Gaussian-RBF kernel while preserving the error rate performance. Experimental results validate the cost-effectiveness of the developed authentication system. In numbers, the fast-KRR learning model achieves an equal error rate (EER) of 1.39% with O(N) training time, while SVM with the RBF kernel shows an EER of 1.41% with O(N 2 ) training time. In this paper, a fast kernel ridge regression (KRR) learning algorithm is adopted with ( ) training cost for large-scale active authentication system. A truncated Gaussian radial basis function (TRBF) kernel is also implemented to provide better cost-performance tradeoff. The fast-KRR algorithm along with the TRBF kernel offers computational advantages over the traditional support vector machine (SVM) with Gaussian-RBF kernel while preserving the error rate performance. Experimental results validate the cost-effectiveness of the developed authentication system. In numbers, the fast-KRR learning model achieves an equal error rate (EER) of 1.39% with ( ) training time, while SVM with the RBF kernel shows an EER of 1.41% with ( ) training time. In this paper, a fast kernel ridge regression (KRR) learning algorithm is adopted with O(N) training cost for largescale active authentication system. A truncated Gaussian radial basis function (TRBF) kernel is also implemented to provide better cost-performance tradeoff. The fast-KRR algorithm along with the TRBF kernel offers computational advantages over the traditional support vector machine (SVM) with Gaussian-RBF kernel while preserving the error rate performance. Experimental results validate the cost-effectiveness of the developed authentication system. In numbers, the fast-KRR learning model achieves an equal error rate (EER) of 1.39% with O(N) training time, while SVM with the RBF kernel shows an EER of 1.41% with O(N2) training time. |
| Author | Chi-Chen Fang Sun-Yuan Kung Chang, Jien Morris Pei-Yuan Wu |
| Author_xml | – sequence: 1 surname: Pei-Yuan Wu fullname: Pei-Yuan Wu email: peiyuanwu1987@gmail.com organization: Dept. of Electr. Eng., Princeton Univ., Princeton, NJ, USA – sequence: 2 surname: Chi-Chen Fang fullname: Chi-Chen Fang email: cfang@iastate.edu organization: Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA – sequence: 3 givenname: Jien Morris surname: Chang fullname: Chang, Jien Morris organization: Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA – sequence: 4 surname: Sun-Yuan Kung fullname: Sun-Yuan Kung organization: Dept. of ECE, Princeton Univ., Princeton, NJ, USA |
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| SubjectTerms | Active authentication Algorithms Authentication Basis functions Biomedical monitoring cost-effective Feature extraction Kernel Kernel functions kernel methods kernel ridge regression (KRR) Keyboards keystroke Machine learning Radial basis function support vector machine (SVM) Support vector machines Training truncated-radial basis function (TRBF) |
| Title | Cost-Effective Kernel Ridge Regression Implementation for Keystroke-Based Active Authentication System |
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