Malware detection is one of the leading security issues in Network Security paradigm. There exist different malware families. All of the families of malware are even not completely discovered.. In case of an unknown malware family of attack detection is various challenging tasks. In the current trend of malware detection used some data mining technique such as classification and clustering. The process of classification improves the process of detection of malware. In this paper used graph based technique for malware classification and detection. The graph based technique used for a feature collection of different malware data. The proposed algorithm is very efficient in compression of pervious method.
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