Towards Building Generalizable Models for Malware Detection
Date:
Presented a poster on using meta-learning techniques to improve malware detection across unseen malware families. The project integrates Model-Agnostic Meta-Learning (MAML) with datasets like BODMAS, MaleVis, and Avast-CTU to enhance model generalization in cybersecurity contexts.
