Robust ML Models Against Adversarial Malware in E-Commerce

This coursework explores malware detection in e-commerce, focusing on the rising threats posed by adversarial attacks. It begins with an introduction to the necessity for advanced fraud detection models, followed by a literature review of current detection techniques, including machine learning approaches. Lastly, it proposes innovative defensive mechanisms, such as adversarial training and hybrid strategies, while addressing gaps in current research.