International Journal of Soft Computing

Year: 2014
Volume: 9
Issue: 3
Page No. 117 - 121

A Self Learning Algorithm for Anomaly Based Intrusion Detection System using Genetic Neural Network

Authors : M. Ravichandran and C.S. Ravichandran

References

Das, A., D. Nguyen, J. Zambreno, G. Memik and A. Choudhary, 2008. An FPGA-based network intrusion detection architecture. IEEE Trans. Inform. Forens. Secur., 3: 118-132.
CrossRef  |  Direct Link  |  

Jiang, H. and J. Ruan, 2009. The application of genetic neural network in network intrusion detection. J. Comput., 4: 1223-1230.
CrossRef  |  Direct Link  |  

Li, W., 2004. Using genetic algorithm for network intrusion detection. Proceedings of the United States Department of Energy Cyber Security Group 2004 Training Conference, May 24-27, 2004, Kansas City, Kansas, USA., pp: 1-8.

Tian, J. and M. Gao, 2009. Network intrusion detection method based on high speed and precise genetic algorithm neural network. Proceedings of ACM International Conference on Networks Security, Wireless Communications and Trusted Computing, 2009, Volume 2, April 25-26, 2009, Wuhan, Hubei, pp: 619-622.

Vesely, A. and D. Brechlerova, 2004. Neural networks in intrusion detection systems. Agric. Econ. Czech, 50: 35-39.
Direct Link  |  

Design and power by Medwell Web Development Team. © Medwell Publishing 2024 All Rights Reserved