All Title Author
Keywords Abstract

Immunodominance-based Clonal Network Clustering Algorithm for Intrusion Detection

Keywords: Immunodominance,Non-uniform mutation,Clonal selection,Forbidden clone,Evolutionary network,Intrution dctctlion

Full-Text   Cite this paper   Add to My Lib


According to the idea of intelligent complementary fusion, a combination of immunodominance, inverse operation, clonal selection, non-uniform mutation and forbidden clone was employed in a novel clustering method with network structure for intrusion detection. The clustering process was adjusted in accordance with affinity function and evolution strategics. So an intelligent, self-adaptive and self-learning network was `evolved' to reflect the distribution of original data. Then the minimal spanning tree was employed to perform clustering analysis and obtain the classification of normal and anormal data. I}he simulations through the KDD CUP99 dataset show that the novel method can deal with massive unlabeled data to distinguish normal case and anomaly and even can detect unknown intrusions effectively.


comments powered by Disqus