Detection of malware infection using score level fusion with Kernel Fisher Discriminant Analysis

The malware attack is increasing in both breadth and depth, and damage from botnets, whose activities are unabated, and infections from the Web have recently increased. We therefore studied the malware infection detection method by comparing malware traffic with normal traffic. We propose the malware infection detection using score level feature fusion with Kernel Fisher Discriminant Analysis.