Microsoft is developing ways to use machine learning to turn attackers’ specific approaches to compromising targeted systems into models of behavior that can be used to automate the attribution of attacks to specific actors and predict the most likely next attack steps. In a research blog published earlier this month, the software giant stated it has used data collected on threat actors through its endpoint and cloud security products to train a large, probabilistic machine-learning model that can associate a series of tactics, techniques and procedures (TTPs) — the signals defenders can glean from an ongoing cyberattack — with a specific group.

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