Improved Malware Detection Technique Using Ensemble Based Classifier and Graph Theory

Malware classification and detection process is a very complex process in network security. In current network security scenario various types of malware family are available, some are known family and some are unknown family. The family of knowing malware detection used some well know technique such as signature based technique and rule based technique. 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.