Cobalt Iron Inc. has recently announced that it has been granted a patent on its technology for machine learning (ML) optimization of authentication control. The patent describes new capabilities for Cobalt Iron Compass. The platform already has the ability to optimize user authentication and access to IT resources dynamically based on what’s happening in the environment. This new patent extends that capability by applying new ML techniques —adding yet another layer of intelligence and security to enterprise IT resources and operations.

These new patented ML techniques continuously improve authentication controls over time, learning from the results of previous controls. What’s more, the technology automatically adjusts authorization controls based on conditions, events, project status, access activities, etc. This eliminates the pervasive security risks of outdated and unresponsive authorization controls and makes the entire IT infrastructure more secure and smarter.

The techniques disclosed in this patent are:

– Collecting training data, including environment event data, user permission access patterns, access control duration data, security events and alerts, project data, cyber event information, security event logs, data protection operational results, and the like.

– Analyze training data to determine the effectiveness of authentication controls during past conditions and events.

– Generate ML rules to potentially adjust authentication controls during future conditions and events.

– Monitor various conditions and events, including environmental events.

– Dynamically adjust user authentication privileges based on generated ML rules.

– Modify the duration of user authentication privilege settings in response to generated ML rules.

“Today’s authentication control practices can’t keep up with continually changing business environments, and that can easily lead to security risks,” said Richard Spurlock, CEO and founder of Cobalt Iron. “The novel techniques in this patent use extensive data collection, analytics, and machine learning to adjust user authentication and access to IT resources dynamically based on environmental events and operational outcomes. Not only does this mean that IT infrastructures and business security controls become more intelligent over time, but they automatically adjust themselves to continue meeting business security and safety needs.”