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Detecting Network Anomalies in Mixed-Attribute Data Sets

Tran, Khoi-Nguyen; Jin, Huidong (Warren)


Detecting network anomalies is important part of intrusion detection systems that have been developed with great successes on homogeneous data. There have been successes with mixed-attribute data using various techniques, however, few of them exist for using mixed-attribute data without further manipulation or consideration of dependencies among the different types of attributes. We propose in this paper a fusion of decision tree and Gaussian mixture model (GMM) to detect anomalies in...[Show more]

CollectionsANU Research Publications
Date published: 2010
Type: Conference paper
Source: Proceedings of the Third International Conference on Knowledge Discovery and Data Mining
DOI: 10.1109/WKDD.2010.96


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