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논문검색

Application of Improved BP Neural Network with Correlation Rules in Network Intrusion Detection

초록

영어

To detect various network attacks in real time, this paper developed a network intrusion detection system based on artificial neural network. This paper first introduced the recent development of neural network, BP algorithm and structure of a simple perceptron. Then, this paper developed an improved BP neural network algorithm to detect anomaly network traffic with adjusted correlation rules. Finally, the network intrusion system in this paper was tested in a real network situation; the improved BP algorithm neural network with adjusted correlation rules shows a reduction in total error and increment in alarm rate compared to the traditional basic BP algorithm model.

목차

Abstract
 1. Introduction
 2. Methods
  2.1. Improvement of the Basic BP Algorithm
  2.2. Correlation Analysis
  2.3. The Process of Network Intrusion Detection
 3. Results
 4.Conclusion
 Acknowledgments
 References

저자정보

  • Yongfeng Cui School of Science and Technology, Zhoukou Normal University, Zhoukou Henan 466001, China
  • Xiangqian Li Ma Network Centre, Zhoukou vocational and technical college, Zhoukou Henan 466000, China
  • Zhijie Liu Library, Zhoukou Normal University, Zhoukou Henan 466001, China

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