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Cost-effective kernel ridge regression implementation for keystroke-based active authentication system
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
In this study a keystroke-based authentication system is implemented on a large-scale free-text keystroke data set, where cost effective kernel-based learning algorithms are designed to enable trade-off between computational cost and accuracy performance. The authentication process evaluates the user's typing behavior on a vocabulary of words, where the judgments based on each word are concatenated by weighted votes, whose weights are also trained to provide optimal fusion of independentdoi:10.1109/icassp.2014.6854761 dblp:conf/icassp/WuFCGK14 fatcat:hkyp3feshnan5iw35uh3xhcvta