A Plurilock Profile is an evolving body of data about individual characteristics that is used to authoritatively identify a user.

Plurilock's machine learning engine assembles user profiles by combining and analyzing behavioral-biometric movement patterns alongside environmental and contextual data through a brief process called enrollment. Profile data is numeric, statistical, and individually unique in nature—every profile is unique, just as every fingerprint is unique.

During login attempts or sessions protectecd by Plurilock, the user's current movement patterns, environment, and context are compared to those stored in the user's profile. If they aren't consistent with one another, authentication fails.

Machine learning enables Plurilock profiles to change over time along with the user; profiles are constantly updated as the user's habits and patterns gradually evolve.