Threshold-based clustering with merging and regularization in application to network intrusion detection
Signature-based intrusion detection systems look for known, suspicious patterns in the input data. In this paper we explore compression of labeled empirical data using threshold-based clustering with regularization. The main target of clustering is to compress training dataset to the limited number of signatures, and to minimize the number of comparisons that are necessary to determine the status of the input event as a result. Essentially, the process of clustering includes merging of the...[Show more]
|Collections||ANU Research Publications|
|Source:||Computational Statistics and Data Analysis|
|01_Nikulin_Threshold-based_clustering_2006.pdf||238.15 kB||Adobe PDF||Request a copy|
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