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Profile

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 protected 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.

2FA/MFA Rapid Reference

Authentication at a glance

Download the 2FA/MFA Rapid Reference now:

  • 2FA and MFA basics and common solutions
  • The benefits and drawbacks of each
  • Glossary of authentication terms

 

2FA/MFA Rapid Reference

  • 2FA and MFA basics and common solutions
  • The benefits and drawbacks of each
  • Glossary of authentication terms
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Downloadable References

PDF
Sample, shareable addition for employee handbook or company policy library to provide governance for employee AI use.
PDF
Generative AI is exploding, but workplace governance is lagging. Use this whitepaper to help implement guardrails.
PDF
Cheat sheet for basics to stay secure, their ideal deployment order, and steps to take in case of a breach.
PDF
Real-time, continuous authentication using behavioral biometrics and machine learning.
 
 
 
 
 

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