Earticle

초록

영어

Rapid Propagation of malicious program has caused great harm to the security of user information, the traditional way of killing methods, which is lagging behind and non-intelligent, has been unable to meet the demand of current detection. Studying the new malicious detection method on Windows Platform, screening out intelligent detection rules model feature of malicious executable and extracting the new malicious program detection methods based on data mining. Introducing the sample data processing and feature selection process, analyzing and simulating the new classification method, the result shows that the malicious program model can effectively improve the detection accuracy and reduce the rate of false negatives and false positives.

목차

Abstract
 1. Introduction
 2. The Key Technology
  2.1 Malicious Programs
  2.2 Data Mining
 3. Sample Data Processing
  3.1 Sample Data Screening
  3.2 Sample Data Standardization
  3.3 Sample Data Analysis and Processing
 4. Screening of New Features
  4.1 Delete the Data of the Same Attributes and the Data of Linear Correlation between Attributes
  4.2 Redundant Data Processing
 5. Feature Evaluation
 6. Extract Rules
 7. Epilogue
 Acknowledgements
 References

키워드

저자

• Haixu Xi [ Jiangsu University of Technology, No.1801, Zhongwu Avenue, Changzhou City, Jiangsu Province, China ]
• Hongjin Zhu [ Jiangsu University of Technology, No.1801, Zhongwu Avenue, Changzhou City, Jiangsu Province, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605