Investigating the robustness against transferable adversarial attacks of learning-based network intrusion detection system

RESEARCH CREW
22:23 06/11/2024
TIN LIÊN QUAN
Malware threatens cybersecurity by enabling data theft, unauthorized access, and extortion. Traditional malware detection systems (MDS) struggle with the increasing volume and complexity of malware. While machine learning (ML) and deep learning (DL) offer promising solutions, they remain vulnerable to adversarial attacks that evade detection. Recent research focuses on developing...