The power of amnesia: learning probabilistic automata with variable memory length
Machine Learning - Special issue on COLT '94
Making large-scale support vector machine learning practical
Advances in kernel methods
An introduction to intrusion detection
Crossroads - Special issue on computer security
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Using the Fisher Kernel Method to Detect Remote Protein Homologies
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
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Detecting user to root attacks is an important intrusion detection task This paper uses a mix of spectrum kernels and probabilistic suffix trees as a possible solution for detecting such intrusions efficiently Experimental results on two real world datasets show that the proposed approach outperforms the state of the art Fisher kernel based methods in terms of speed with no loss of accuracy.