Check out MIT's Human-Machine Hybrid for Cybersecurity

A group of MIT researchers has sketched out a way to address a gap in cybersecurity that exists between human and machine. Human-made rules, which are meant to alert the system of an attack, don't work unless an attack exactly matches one of those rules. Machine-learning measures typically rely on anomaly detection. Consequently, false alarms aren't uncommon and the system starts to distrust itself. Combine these two forces - man and machine - and that's when magic can happen, according to a group of researchers out of MIT's Computer Science and Artificial Intelligence Lab (CSAIL).