The Research of Intrusion Detection System Based on ANN on Cloud Platform

Abstract:

Intrusion detection system (IDS) can find the intrusion information before the computer be attacked, and can hold up and response the intrusion in real time. Artificial neural network algorithms play a key role in IDS. The intrusion detection system (ANN) algorithms can analyze the captured data and judge whether the data is intrusion. In this paper we used Back Propagation (BP) network and Radical Basis Function (RBF) network to the IDS. The result of the experiment improve that The RBF neural network is better than BP neural network in the ability of approximation, classification and learning speed. During the procedure there is a large amount of computes. On cloud platform the calculation speed has been greatly increased. So that we can find the invasion more quickly and do the processing works accordingly.

• Periodical: Applied Mechanics and Materials (Volumes 263-266)
• Pages: 2962-2965
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.263-266.2962
• Online since: December 2012
• Authors: Xue Song Jiang*, Xiu Mei Wei, Yu Shui Geng
• Keywords: Artificial Neural Network (ANN), Cloud Platform, Intrusion Detection System (IDS), RBF Algorithm

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