A neural model in intrusion detection systems

Authors:
Otávio A. S. Carpinteiro;Roberto S. Netto;Isaías Lima;Antonio C. Zambroni de Souza;Edmilson M. Moreira;Carlos A. M. Pinheiro
Affiliations:
Research Group on Computer Networks and Software Engineering, Federal University of Itajubá, Itajubá, MG, Brazil;Research Group on Computer Networks and Software Engineering, Federal University of Itajubá, Itajubá, MG, Brazil;Research Group on Computer Networks and Software Engineering, Federal University of Itajubá, Itajubá, MG, Brazil;Research Group on Computer Networks and Software Engineering, Federal University of Itajubá, Itajubá, MG, Brazil;Research Group on Computer Networks and Software Engineering, Federal University of Itajubá, Itajubá, MG, Brazil;Research Group on Computer Networks and Software Engineering, Federal University of Itajubá, Itajubá, MG, Brazil
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Year:
2006

Citing 9
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Neural Networks: A Comprehensive Foundation

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Training a neural-network based intrusion detector to recognize novel attacks

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A comparison of neural projection techniques applied to intrusion detection systems

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Abstract

The paper proposes the use of the multilayer perceptron model to the problem of detecting attack patterns in computer networks. The multilayer perceptron is trained and assessed on patterns extracted from the files of the Third International Knowledge Discovery and Data Mining Tools Competition. It is required to classify novel normal patterns and novel categories of attack patterns. The results are presented and evaluated in the paper.