Survey on Clustering Algorithm & Diagnosing Unsupervised Anomalies for Network Security

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Provided by: Inpressco
Topic: Big Data
Format: PDF
Data clustering is a process of putting similar data into groups. A clustering algorithm partitions a data set into several groups such that the similarity within a group is larger than among groups. This paper reviews four types of clustering techniques k-means clustering, k-median clustering, density based clustering and filtered clustered. Performance of the 4 techniques are presented and compared. In this paper, the authors also discussed completely unsupervised approach to detect the attack, without relying on signature, labeled traffic & training.
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