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作者:

Lai, Ying-Xu (Lai, Ying-Xu.) (学者:赖英旭)

收录:

EI Scopus PKU CSCD

摘要:

Machine learning or data mining method can identify new or unknown malicious executables with some degree of success. Feature selection is a key to applying data mining or machine learning to detect malicious executables. In order to improve detecting accuracy, a new method of extracting most representative features is purposed. The new classifier based on strings achieves has high detection rates and can be expected to perform well in real-world conditions.

关键词:

Data mining Feature extraction Machine learning

作者机构:

  • [ 1 ] [Lai, Ying-Xu]College of Computer Science, Beijing University of Technology, Beijing 100124, China

通讯作者信息:

  • 赖英旭

电子邮件地址:

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来源 :

Journal of Beijing University of Technology

ISSN: 0254-0037

年份: 2009

期: 12

卷: 35

页码: 1703-1709

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

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