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Mining Anomaly using Association Rule
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 67 - Number 24 |
| Year of Publication: 2013 |
| Authors: Mahadik Priyanka V., Kosbatwar Shyam P. |
10.5120/11734-7338
|
Mahadik Priyanka V., Kosbatwar Shyam P. . Mining Anomaly using Association Rule. International Journal of Computer Applications. 67, 24 ( April 2013), 9-12. DOI=10.5120/11734-7338
Abstract
In a world where critical equipments are connected to internet, hence protection against professional cyber criminals is important. Today network security, uptime and performance of network are important and serious issue in computer network. Anomaly is deviation from normal behavior which is factor that affects on network security. So Anomaly Extraction which detects and extracts anomalous flow from network is requirement of network operator. Using Histogram based detector to identify anomalies and then applying Association rule mining, anomalies will extracted. Apriori algorithm will use to generate the set of rule applied on metadata. Identification and Extraction of anomalous flow can be used for useful application e. g. Root cause analysis, Network forensics, Modeling anomalies etc.
References
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