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Network Security Prediction Method Based on Kalman Filtering Fusion Decision Entropy Theory

초록

영어

Network security situation prediction is of great significance for the use of the Internet, and it is the focus of production and life issues. Under the guidance of the model combination forecasting method, In this paper, based on the Kalman filtering model a new method of network security prediction is presented, which is based on the theory of decision entropy. In this method, the Kalman state equation and measurement equation are constructed according to the key attributes of the network security state, and then combined with the decision entropy theory to predict the future state of network security. The experimental results show that the proposed method has high prediction accuracy and is suitable for the state prediction of network security.

목차

Abstract
 1. Introduction
 2. The Network Security Prediction Model
 3. Proposed Network Security Prediction Algorithm
  3.1 Kalman Filtering Algorithm for Network Security Situation
  3.2 The New Information Estimation for Network Security Situation
  3.3 Decision Entropy Fusion Kalman Filtering Network Security Situation Prediction Algorithm
 4. Experimental Results and Analysis
  4.1. Experimental Scene Configuration
  4.2 Network Security Situation Calculation
  4.3 Network Security Situation Prediction
 5. Conclusion
 Reference

저자정보

  • Yunfa Li Key Laboratory of Complex Systems Modeling and Simulation, School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China
  • Mingyi Li Key Laboratory of Complex Systems Modeling and Simulation, School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China
  • Yangyang Shen Key Laboratory of Complex Systems Modeling and Simulation, School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China

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