A New Method for Filtering IDS False Positives with Semi-supervised Classification
作者： Minghua Zhang , Haibin Mei
DOI: 10.1007/978-3-642-31588-6_66
关键词:
摘要: Constructing alert classifiers is an efficient way to filter IDS false positives. Classifiers built with supervised classification technique require large amounts of labeled training alerts which are difficult and expensive prepare. This paper proposes use semi-supervised learning build model reduce the number needed alerts. Experiments conducted on DARPA 1999 dataset have demonstrated that can improve performance dramatically, especially when small. As a result, feasibility deploying classifier for filtering positives enhanced.
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