文章基本信息

标题：Malware detection based on evolving clustering method for classification
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作者：Altyeb Altaher ; Supriyanto ; Ammar ALmomani 等
期刊名称：Scientific Research and Essays
印刷版ISSN：1992-2248
出版年度：2012
卷号：7
期号：22
页码：2031-2036
DOI：10.5897/SRE12.001
语种：English
出版社：Academic Journals
摘要：Malware is a computer program that can replicate itself and cause potential damage in data files. The high speed of the computers and networks increased the virus spread. To avoid the virus infection and the data loss, it is important to use an efficient and effective method for virus detection. This paper proposes an approach for malware detection based on the evolving clustering method. The proposed approach effectively combined the information gain method as a feature selector with the evolving clustering method as evolving learning classifier. Based on the experimental results, the proposed malware detection approach proved its capability to detect the malware by decreasing the false positive rate to 1% while increasing the level of accuracy to 99%.
关键词：Malware detection; network security; intelligent classification; information gain