Anomaly Intrusion Detection Using Incremental Learning of an Infinite Mixture Model with Feature Selection [chapter]

Wentao Fan, Nizar Bouguila, Hassen Sallay
2013 Lecture Notes in Computer Science  
We propose an incremental nonparametric Bayesian approach for clustering. Our approach is based on a Dirichlet process mixture of generalized Dirichlet (GD) distributions. Unlike classic clustering approaches, our model does not require the number of clusters to be pre-defined. Moreover, an unsupervised feature selection scheme is integrated into the proposed nonparametric framework to improve clustering performance. By learning the proposed model using an incremental variational framework, the
more » ... number of clusters as well as the features weights can be automatically and simultaneously computed. The effectiveness and merits of the proposed approach are investigated on a challenging application namely anomaly intrusion detection.
doi:10.1007/978-3-642-41299-8_35 fatcat:fzjku6yiufh63a2r4pu2pk2s4q