Memory Analysis for Malware Detection: A Comprehensive Survey Using the OSCAR Methodology
Malware has sharply escalated, with a 30% surge in global cyberattacks in 2024, highlighting the limitations of traditional detection methods against sophisticated threats. This survey addresses gaps in prior work by applying the OSCAR methodology to review memory acquisition techniques, forensic methods, and malware detection approaches, providing the most diverse taxonomy to date. It also evaluates memory dump datasets and categorizes detection methods, including both traditional and machine learning approaches, highlighting their accuracy, benefits, drawbacks, and challenges.