This analyst/machine interaction creates a loop where the more attacks the AI system predicts, the more feedback/training it receives, which in turn improves the accuracy of future predictions. The primary benefits of the analyst/machine loop are to reduce the time to detection while working within the limited time the analyst has.
And when a predictive model is learned at one customer, it can be transferred to the entire network, creating a strong network effect. This enables customers to share intelligence at a behavioral level as opposed to sharing on an entity level. Entities such as IP addresses or domains are easily gamed by the attackers, while behavioral signatures are not.
Given the limitations of current technology and the chronic drought of InfoSec professionals, there is a need for a new approach. The goals of such a solution are clear: work within the limited time an analyst has; detect both new and emerging attacks; reduce the time to detection; and reduce false positives. AI, achieved through the combination of man and machine, may well be the answer.
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