System predicts 85 percent of cyber-attacks using input from human experts
Monday, April 18, 2016 - 17:10
in Mathematics & Economics
Today's security systems usually fall into one of two categories: human or machine. So-called "analyst-driven solutions" rely on rules created by living experts and therefore miss any attacks that don't match the rules. Meanwhile, today's machine-learning approaches rely on "anomaly detection," which tends to trigger false positives that both create distrust of the system and end up having to be investigated by humans, anyway.