Paper Title: PE Header-Based Multinomial Malware Classification Using ML for Computing Systems
Conference Name: 한국통신학회 학술대회논문집 - Korean Institute of Communications and Information Sciences (KICS Summer 2023)
Abstract: Malware is an envelope of various malicious software or programs which hackers use to harm and attack computer systems.
Malware detection is the procedure of identifying the computer vulnerability and tracing the malicious files to discover the malware and, thus, secure the computing system.
However, detecting and classifying the malware manually is almost impossible and time-consuming.
This paper introduces a Portable Executable (PE) header-based approach for detecting malicious programs to handle the issue.
Various Machine Learning (ML) algorithms are applied and compared to the performance to detect malware types.