Self-Learning AI is made up of many thousands of algorithms that inform its decision-making, each with different strengths. These algorithms operate in competition with one another to deliver the best model for every user and device.
To determine which algorithms to employ at any given moment, Darktrace uses a smart threshold filter that contextually weights and rescores the outputs from all machine learning detectors in light of their previous performance.
To combine these analyses of digital activity, Darktrace uses a technique known as Recursive Bayesian Estimation. Crucially, this allows the AI to continually recalculate threat levels in light of new data and discern significant patterns in data flows indicative of attacks.