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System Predicts 85 Percent of Attacks Using Human Experts
“Analyst-driven solutions” rely on rules created by living experts and miss attacks that don’t match the rules. Machine-learning approaches rely on “anomaly detection,” which triggers false positives needing investigation by humans.
Protecting Individual Data | Protecting Systems | Safeguarding the Connected World | Massachusetts Institute of Technology