Unsupervised Clustering Methods for Identifying Rare Events in Anomaly Detection

Provided by: World Academy of Science, Engineering and Technology
Topic: Security
Format: PDF
It is important problems to increase the detection rates and reduce false positive rates in Intrusion Detection System (IDS). Although preventative techniques such as access control and authentication attempt to prevent intruders, these can fail, and as a second line of defense, intrusion detection has been introduced. Rare events are events that occur very infrequently, detection of rare events is a common problem in many domains. In this paper, the authors propose an intrusion detection method that combines rough set and fuzzy clustering. Rough set has to decrease the amount of data and get rid of redundancy.

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