Malware Detection Techniques Base on Variable-Length Opcode Sequences and Rough Set Attribute Reduction
Feng Ben-hu · 2013
In order to solve the problems of increase and separation features in fixed-length Opcode sequences,we propose a malware detection techniques base on variable-length Opcode sequences and rough set attribute reduction theory,using vaiable-length Opcode sequences can effectively solve the problem of separation features,and in order to effectively reduce the scale of features,we only consider the Opcode sequences which composed of the commonly used 13 instruction,afterwards we use rough set theory to reduct its,at last we get the features dimension is very low and contrast to fixed-length sequence of instructions,we get th higher classification accuracy,and false negative rate is lower from experiments ultimately.