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
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