Design Simulation and Analysis of Intelligent Malware Detection Using Machine Learning Approach

Abstract

With the rapid advancement in cyber threats, malware detection has become an essential task in securing information systems. Traditional signature-based detection methods have become increasingly ineffective due to the evolving nature of malware. The advent of machine learning (ML) offers a promising alternative by enabling systems to identify and classify unknown malware based on patterns in their behaviors. This paper presents the design, simulation, and analysis of an intelligent malware detection system using machine learning techniques. Various machine learning algorithms, including supervised and unsupervised approaches, are evaluated for their effectiveness in malware detection. The results indicate that machine learning provides a robust and adaptive solution to combating modern malware threats.