Earticle

초록

영어

With the rapid development of the Internet, especially the development of mobile Internet, network size and network infrastructure changes, especially the more random access node to detect network attacks challenges traditional detection algorithm using neural networks, so that the calculated volume increased dramatically, and will detection accuracy is not high, for this problem, we use the stochastic process theory hidden Markov chain transformation neural network, so that the convergence of a substantial decline, while improving network attack detection accuracy degree.

목차

Abstract
 1. Introduction
 2. Related Works
  2.1. Intrusion Detection
  2.2. Stochastic Model Theory of Artificial Intelligence
  2.3. The Neural Network Theory
 3. Based on Hidden Markov Model and Neural Network Intrusion Detection Model
 4. The Model and the Analysis of Experimental Results
  4.1. The Model
  4.2. Experimental Analysis
 5. Conclusion
 6. Fund Support (1)(2)
 References

키워드

저자

• Yunfeng Yang [ College of Computer & Information Engineering, Hechi University, Yizhou, China ]
• Fengxian Tang [ College of Computer & Information Engineering, Hechi University, Yizhou, China ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605