Abstract

Malware is one of the all told the foremost security threats on the net now a days. Some of the Internet problems like denial of service attacks and spam e-mails have malware threat cause. Computers involved with malware are however networked together for making botnets, and major of threats or attacks are basically launched with the help of these types of malicious and attacker-controlled networks. Downloading files like Executable files like .exe, .bat, .msi etc from sources of untrusted internet probably having an opportunity of getting maliciousness. Further it is seen that these executables are smartly obfuscated with the help of some of the anomalous user for bypassing antivirus stuffs. In this research work , we have proposed an enhanced approach for detecting some of the malicious executables files with the help of analysing the traced Portable Executable (PE) files which are extracted from executable files and use of PCA feature extraction method. The method used in this paper consists of training a supervised binary classifier with the help of these extracted features from the portable executables files from the normal and malicious executables. Considering this approach experimentation has been done on an outsized publicly available dataset and it is seen that over 95% of classification accuracy can be obtained.

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