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ABSTRACT
Title |
: |
Intrusion Detection using unsupervised learning |
Authors |
: |
Kusum bharti, Sanyam Shukla, Shweta Jain |
Keywords |
: |
Feature selection, k-mean clustering, fuzzy k mean
clustering, and KDDcup 99 dataset |
Issue Date |
: |
August 2010 |
Abstract |
: |
Clustering is the one of the efficient datamining
techniques for intrusion detection. In clustering algorithm kmean
clustering is widely used for intrusion detection. Because it
gives efficient results incase of huge datasets. But sometime kmean
clustering fails to give best result because of class
dominance problem and no class problem. So for removing these
problems we are proposing two new algorithms for cluster to
class assignment. According to our experimental results the
proposed algorithm are having high precision and recall for low
class instances. |
Page(s) |
: |
1865-1870 |
ISSN |
: |
0975–3397 |
Source |
: |
Vol. 2, Issue.5 |
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