Machine learning is everywhere in the world of cybersecurity these days. It is often thought of as the magic bullet to secure systems and networks. Machine learning classifiers perform much better in the supervised case, where labeled data is available. But what happens in the real world where these labeled examples are not available? The ideal purpose of a machine learning algorithm is to create a situation where unknown attacks are identified and analysts are alerted. IBM Executive Report: Cybersecurity in the cognitive era in cognitive era of cognitive era.”]