Malware Detection in PE files using Machine Learning
Samarth Tyagi, Achintya Baghela, Kashif Majid Dar, Anwesh Patel, Sonali Kothari, Snehal Bhosale · 2023
Malware has become one of the most challenging threats to the computer domain. Malware is malicious code mainly used to gain access and collect confidential information without permission. The internet coverage has boomed a lot in today’s time leading to people downloading various files and installing executable files like.exe,.bat, and.msi files. This leads to many complications as these files are the vector for malicious code. Through this paper, we present a technique to detect executable files as malicious by a detailed search of the Portable Executable (PE) files that come along with the executable files. Our approach uses the static analysis technique to get features from PE files. We use these with supervised learning algorithms to classify malware. We also compare the performance of different algorithms to determine the best way to approach our problem.