The nature of statistical learning theory
The nature of statistical learning theory
Statistical methods for speech recognition
Statistical methods for speech recognition
Exploiting generative models in discriminative classifiers
Proceedings of the 1998 conference on Advances in neural information processing systems II
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Using the Fisher Kernel Method to Detect Remote Protein Homologies
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
Automated Generation and Analysis of Attack Graphs
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
Intrusion detection using sequences of system calls
Journal of Computer Security
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This paper addresses the taskof detecting intrusions in the form of malicious attacks on programs running on a host computer system by inspecting the trace of system calls made by these programs. We use 'attack-tree' type generative models for such intrusions to select features that are used by a Support Vector Machine Classifier. Our approach combines the ability of an HMM generative model to handle variable-length strings, i.e. the traces, and the non-asymptotic nature of Support Vector Machines that permits them to workw ell with small training sets.