Abstract
Identifying the intrusion attempts of the monitored systems is extremely vital for the next generation intrusion detection system. In this paper, a novel network intrusion attempts prediction model (FNNIP) is developed, which is based on the observation of network packet sequences. A new fuzzy neural network based on a novel BP learning algorithm is designed and then applied to the network intrusion attempts predicting scheme. After given the analysis of the features of the experimental data sets, the experiment process is detailed. The experimental results show that the proposed Scheme has good accuracy of predicting the network intrusion attempts by observing the network packet sequences.
This research was supported by the National High Technology Development 863 program of China under Grant No. 2002AA142010.
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Zhang, G., Sun, J. (2006). A Novel Network Intrusion Attempts Prediction Model Based on Fuzzy Neural Network. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science – ICCS 2006. ICCS 2006. Lecture Notes in Computer Science, vol 3991. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11758501_58
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DOI: https://doi.org/10.1007/11758501_58
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