Earticle

초록

영어

In this paper, in order to assess the risk of network, network security assessment process being involved in the content in detail. The above-mentioned research-based support system platform security test and evaluate research of the safety situation assessment. Prediction subsystem detailed design and carry out the implementation. In this paper, network security issues, as a detailed study of neural networks knowledge. Focus on the evaluation methods and calculation rules of nerve network technology, it has been studied by specific examples. Calculation demonstrated the feasibility of neural network evaluation model through actual case, which pointed out the traditional methods. This paper focuses on the network security assessment based on neural network technology, extensive analysis of the proposed major modeling tool indicator system for network security analysis. The application of neural networks was a network security assessment and to optimize the network by genetic algorithm. The key parameter combination operated efficiency of neural networks to get better play.

목차

Abstract
 1. Introduction
 2. Basic Theoretical of Information Security Assessments
  2.1 Characteristics of Complex Network Metrics
  2.2 Risk Factors
  2.2 Genetic Algorithm and BP Neural Networks
 2. Complex Network Security Evaluation Modeling based on GABP Algorithm
  2.1 Improved Modeling of GABP Algorithm
  2.2 Lateral Distribution Structure of the System
 4. Experiment and Results
  4.1 Data Processing
  4.2 Analysis of Results
  4.2 Comparison GABP Algorithms and Several other Models
 5. Conclusions
 References

키워드

저자

• Ranbeer Tyagi [ Research Scholar, Deptt. of Electronics & Communication UTU, Dehradun (Uttarakhand), India ]
• Geetam Singh Tomar [ Deptt. of Electronics & Communication THDC -IHET, Tehri Garhwal Uttarakhand, India ]
• Namkyun Baik [ Korea Internet & Security Agency, Korea ] 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