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A self-organizing map and its modeling for discovering malignant network traffic

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6 Author(s)
Langin, C. ; Dept. of Comput. Sci., Southern Illinois Univ., Carbondale, IL ; Hongbo Zhou ; Rahimi, S. ; Gupta, B.
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Model-based intrusion detection and knowledge discovery are combined to cluster and classify P2P botnet traffic and other malignant network activity by using a self-organizing map (som) self-trained on denied Internet firewall log entries. The SOM analyzed new firewall log entries in a case study to classify similar network activity, and discovered previously unknown local P2P bot traffic and other security issues.

Published in:

Computational Intelligence in Cyber Security, 2009. CICS '09. IEEE Symposium on

Date of Conference:

March 30 2009-April 2 2009