DocumentCode :
260967
Title :
Anomaly extraction using association rule with the heterogeneous detectors
Author :
Dharmadhikari, Madhavi ; Kolhe, V.L.
Author_Institution :
Dept. of Comput. Eng., Univ. of Pune, Pune, India
fYear :
2014
fDate :
27-28 Feb. 2014
Firstpage :
1
Lastpage :
4
Abstract :
Anomaly detection techniques are used to detect the abnormal behavior. It is also used to identify security attack. The proposed system finds flows those are anomalous from the state of flows. Apriori algorithm is uses to identify anomalous flows which are present in network traffic. In this proposed method, first preprocessing of input traffic flow is done; Apriori algorithm is applied over network traffic flows are detecting. Heterogeneous detectors are applied on frequent item set to And anomalous flow. It enhances the performance in terms of speed as well as detection accuracy.
Keywords :
computer network security; data mining; telecommunication traffic; abnormal behavior; anomalous flows; anomaly detection techniques; anomaly extraction; apriori algorithm; association rule; heterogeneous detectors; input traffic flow; network traffic flows; security attack; Algorithm design and analysis; Association rules; Detectors; Educational institutions; Feature extraction; Intrusion detection; Anomaly detection; Apriori method; Attack; Data mining; Heterogeneous detector;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Communication and Embedded Systems (ICICES), 2014 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-3835-3
Type :
conf
DOI :
10.1109/ICICES.2014.7033908
Filename :
7033908
Link To Document :
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