DocumentCode :
1943191
Title :
Combining Self-Organizing Map Algorithms for Robust and Scalable Intrusion Detection
Author :
Albayrak, Sahin ; Scheel, Christian ; Milosevic, Dragan ; Müller, Achim
Author_Institution :
DAI-Labor, TU Berlin
Volume :
2
fYear :
2005
fDate :
28-30 Nov. 2005
Firstpage :
123
Lastpage :
130
Abstract :
In the field of intrusion detection systems, the aspect of anomaly detection is very important, and consequently there are many approaches that address these security issues. The usage of self-organizing map (SOM) makes a foundation for some of these approaches, which consequently often have problems to cope with the requirements of huge nowadays networks. The proposed approach focuses on improving the usage of SOMs for anomaly detection, by combining the strengths of different SOM algorithms. The performed evaluations have shown the necessity of paying attention to different aspects, coming along with network nodes, to individually choose the best matching SOM for each node´s anomaly detection
Keywords :
security of data; self-organising feature maps; anomaly detection; intrusion detection system; security issues; self-organizing map algorithm; Inspection; Intrusion detection; Invasive software; Laboratories; Neural networks; Organizing; Performance evaluation; Protection; Robustness; Unsupervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-7695-2504-0
Type :
conf
DOI :
10.1109/CIMCA.2005.1631456
Filename :
1631456
Link To Document :
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