Artificial intelligence powered security systems learn from historical activities, incidents, breaches to build their own models autonomously, without constant human supervision.
As organizations grow further, workforce becomes global, diverse, distributed, and enterprises adopt new cloud, on-prem systems and deploy intelligent devices, the old model of static policies based on a fixed set of contexts (for e.g. in the case of access management Time, geo-location, device OS, etc.) starts breaking down. Policies grow in number; context does not show account for past history of users and it becomes arduous to protect against future attack vectors.
This is where AI-powered security starts truly showing value. These types of security systems learn from historical activities, incidents, breaches to build their own models autonomously, without constant human supervision. They are intelligent, in terms of making decisions on their own, and insightful in terms of their ability to look at data both broadly and deeply. They constantly learn and evolve by leveraging new data, so they’re easy to maintain and proactive in nature. This area has evolved by leaps and bounds in the past few years and is critical in the detection and prevention of attacks and breaches. Some of the use cases outlined below.
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