Hybrid Intrusion Detection Model Based on Clustering and Association

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Provided by: International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (IJAREEIE)
Topic: Security
Format: PDF
There are several intrusion detection model are presented till now. But there is still need of betterment in this direction. The authors' paper focuses on the limitation faced in the traditional approach. In this paper, they suggest a hybrid framework based on clustering and association. Clustering is used for separate it on the basis of various classes and on the bases of classes they can classify it. FP growth algorithm is then used as the association classifier which can classify the data accordingly on the same set of category which can be proof to be better in terms of intrusion detection.
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