Digital Biometrics

mSIGNIA invented and patented Digital Biometrics, the newest invention in analytical identity, or aID.  aID uses learning algorithms to understand how data can authenticate a user.  The three main aID authentication methods are:

  • Behavioral Biometrics – analyzes kinesiology (the data of motion) to recognize a user by their typing, swiping, device holding, and other movements
  • Digital Biometrics – analyzes the data a consumer adds to their device, either directly or through their actions such as location, both the data and change in the data are analyzed
  • Social Biometrics – analyzes a user’s identity claims against online data attributed to the user (i.e. credit histories, social media, etc); typically used to protect new accounts and account takeover

A Digital Biometric is unique in that it both identifies the device and the user.  Naturally, since the data is stored on the device, it identifies the device.  However, when a consumer gets a new phone, their Digital Biometric is synchronized to the new device … making a Digital Biometric device independent.

In addition, since a user’s actions change data logged by the device – including location, connected networks, and connected Bluetooth devices – even if one steals all the Digital Biometric from a user’s device and attempts to play-back that data to fraud the system, the data will not change according to the pattern learned from the real user; the fraudster will be detected.

As the table below shows, Digital Biometrics considers 4X the risk data defined for collection in the EMV 3DS specification:

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