Welcome to the repository for research papers on Malware Detection using Machine Learning! This repository compiles various scholarly works and research papers related to the application of machine learning techniques in detecting and classifying malware.
Malicious software, or malware, poses a significant threat to computer systems and networks worldwide. Traditional signature-based detection methods often struggle to keep pace with the rapidly evolving landscape of malware. Machine learning offers a promising approach to enhance malware detection by leveraging patterns and features inherent in malicious code.
This repository aims to serve as a comprehensive resource for researchers, practitioners, and enthusiasts interested in exploring the intersection of machine learning and cybersecurity, particularly in the domain of malware detection.
The repository contains a curated collection of research papers, academic articles, and technical reports covering various aspects of malware detection using machine learning. The papers are categorized and organized for easy navigation and reference.
Contributions to this repository are welcome! If you have authored or come across relevant research papers that you believe should be included, feel free to submit a pull request. Please ensure that the papers adhere to the quality standards and focus on the application of machine learning techniques in malware detection.
The papers included in this repository belong to their respective authors and publishers. This repository is intended for educational and research purposes only. The authors of this repository hold no liability for the use or misuse of the information contained herein.
For inquiries, suggestions, or feedback, please raise an issue.