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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1374

Title: Anomaly Detection in Ethernet Networks Using Self Organizing Maps
Authors: Panigrahy, S K
Mahapatra, J R
Mohanty, J
Jena, S K
Keywords: Intrusion detection
anomaly detection
self organizing map
neural networks
Issue Date: Jan-2011
Publisher: Springer
Citation: International Conference on Advances in Computing, Communication and Control, 2011 (ICAC3'11), P 300-305
Series/Report no.: CCIS;Vol 125
Abstract: Anomaly detection attempts to recognize abnormal behavior to detect intrusions. We have concentrated to design a prototype UNIX Anomaly Detection System. Neural Networks are tolerant of imprecise data and uncertain information. A tool has been devised for detecting such intrusions into the network. The tool uses the machine learning approaches and clustering techniques like Self Organizing Map and compares it with the K-means approach. Our system is described for applying hierarchical unsupervised neural network to intrusion detection system.
Description: Copyright belongs to Proceedings Publisher-Springer Verlag
URI: http://dx.doi.org/10.1007/978-3-642-18440-6_38
http://hdl.handle.net/2080/1374
ISBN: 978-3-642-18439-0
Appears in Collections:Conference Papers

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