Intrusion Detection System Using Fuzzy C-Means Clustering with Unsupervised Learning Via EM Algorithms

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Provided by: VSRD International Journals
Topic: Security
Format: PDF
In present time many intrusions in network and the activities of intrusion is the goal of the security policy system. The unsupervised learning techniques using the machine learning for intrusion detection datasets, the authors know that clustering is the best techniques on the efficient data mining for intrusion detection. The k-mean clustering algorithm is widely used for intrusion detection, because it gives efficient results. But sometime k-mean clustering fails to give best result because if the data set is noisy so for removing these problems they are proposing new algorithms for cluster to class assignment with fuzzy c-means clustering algorithm.
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