Research on Intrusion Detection Method Based on Neural Network

Chi Xu; Jin Chen

doi:10.4028/www.scientific.net/AMR.403-408.1479

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 403-408Research on Intrusion Detection Method Based on...

Research on Intrusion Detection Method Based on Neural Network

Abstract:

This paper describes in Using Self-Organizing Map (SOM) neural networks and its auto-clustering ability to study intrusion detection. The feature pattern of each SOM unit is constructed using PCA feature extraction method and a simplified PCASOM model is proposed. An online learning algorithm is also given and its properties are analyzed. And then the simulation result was given.

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Periodical:

Advanced Materials Research (Volumes 403-408)

Pages:

1479-1482

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.403-408.1479

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Online since:

November 2011

Authors:

Chi Xu, Jin Chen

Keywords:

Access Control (AC), Intrusion Detection, Neural Network (NN)

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References

[1] OjaE. Principal components，minor components，and linear neural networks. Neural Networks, 1992, 5(6): 927-935.

DOI: 10.1016/s0893-6080(05)80089-9

Google Scholar

[2] VonderMC. Network self-organization. In An Introduction to Neural and Electronic Networks，San Diego，CA: Aedemie Press，1990，421-432.

Google Scholar

[3] Kohonen T. Self-Organizing maps(3rdEds. ), Springer-Verlag, Berlin, (2001).

Google Scholar

[4] LeiZ，Yiz. Growing hierarchical principal components analysis self-organizing map. Lecture Notes in Computer Science，ISNN2006，Vol. 3971: 701一706.

DOI: 10.1007/11759966_103

Google Scholar

[5] Beckers J, Ballerini J P. Advanced Analysis of Intrusion Detection Logs[EB/OL]. 2003-06-28.

Google Scholar

[6] Forrest S. A Sense of Self for Unix Process[C]/Proc. of IEEE Symposium on Security and Privacy Proceedings. Oakland CA: IEEE Computer Society Press, (1996).

Google Scholar

[7] Lee W. Learning Patterns from Unix Process Execution Traces for Intrusion Detection[C]/Proc. of AAAI Workshop on AI Approaches to Fraud Detection and Risk Management. Rhode Island: AAAI Press, (1997).

Google Scholar

[8] ITU-T. Control Protocol for Multimedia Communication. ITU-T Recommendation H. 245, 1998-09.

Google Scholar