CyberPoint · Blog · Learning in the Dark: Lessons Learned in Unsupervised Learning

CyberPoint has seen great success in using supervised machine learning for malware detection. A while back, however, some colleagues and I set out to investigate whether we could make any interesting discoveries by applying unsupervised learning to CyberPoint's malware dataset. In supervised learning, one has a set of samples, each with an assigned label. In the field of malware analysis, a sample would typically be a file, and its label might be either benign or the malware family to which it belongs. The goal is: given a new sample, correctly predict its label.