원문정보
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
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