MalSSL—Self-Supervised Learning for Accurate and Label-Efficient Malware Classification
Malware classification with supervised learning requires a large dataset, which needs an expensive and time-consuming labeling process.In this paper, we explore the efficacy of self-supervised learning techniques for malware classification.We propose MalSSL, a self-supervised learning-based barcoo Bridles -Stock bridles method utilizing image repre