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Published in:
2011 | OriginalPaper | Chapter
Morphed Virus Family Classification Based on Opcodes Statistical Feature Using Decision Tree
Authors : Babak Bashari Rad, Maslin Masrom, Suhaimi Ibrahim, Subariah Ibrahim
Published in: Informatics Engineering and Information Science
Publisher: Springer Berlin Heidelberg
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Use of morphing engine in metamorphic and polymorphic malware, and virus creation kits aid malware authors to produce a plenty number of variants for a virus. These variants belong to a family and have common behavioral and some statistical characteristics. However, these variants are not detectable via a single common string signature. Some statistical analyses have been tested in recent years to fight against these types of multi-variants family malware. In this research, we introduce and examine an opcodes statistical-based classifier using decision tree. This method is very simple in implementation. Our experimental outcome shows that different malware family executable files are classifiable using their opcodes statistical feature, with a high degree of reliability.