Abstract:
This paper presents a type of clusteringbased
intrusion detection using single-linkage
clustering algorithm.Basic methods for clustering
include the Linkage based and K-means
techniques.The K-means method generally
produces a more accurate clustering than linkage
based methods, but it has a greater time
complexity and this becomes an extremely
important factor in network intrusion detection
due to very large dataset sizes.Intrusions pose a
serious security risk in a network environment.
Although systems can be hardened against many
types of intrusions, often intrusions aresuccessful
making systems for detecting these intrusions
critical to the security of these system. New
intrusion types, of which detection systems are
unaware, are the most difficult to detect. Singlelinkage
clustering-based intrusion detection
method is able to detect many different types or
intrusions, while maintaining a low false positive
rate as verified over the KDD CUP 1999 dataset.
