A world of digital identification:
the difference between passive and active biometrics

Ever heard about biometrics? Let alone passive and active biometrics? Let’s start with the basics. When talking about digital biometric identification various parameters are considered. This includes characteristic elements of the user such as keyboard input, IP address location, mouse movement, and so much more. Let’s dive into the meaning of the different biometrics. 

Active biometrics

active biometrics

Active biometrics refers to the category of several authentication methods with active participation of an individual. These methods gather information about the individual to verify their unique biological traits and behavioral characteristics and many active biometrics we know from smartphones. Active biometrics involve intentional actions and can include:

  • Voice recognition that analyzes voice pattern to identify if the user actively speaks specific phrases or words.
  • Facial recognition interprets how the user actively presents their face to a camera or sensor capturing their facial features.
  • Fingerprint scanning where the individual actively places their finger on a fingerprint scanner to capture their unique fingerprint patterns.
  • Hand geometry is similar to fingerprint biometrics. The individual places their palm on a scanner which measures and compares the geometric features of their hand including length, width, and shape.


These active biometrics typically rely on advanced sensor technology, algorithms, and databases to gather data for comparison with pre-registered data.

Passive biometrics

Unlike active biometrics, passive biometrics refers to the authentication methods that analyze biological traits and behavioral characteristics without active participation from the individual. Passive biometrics therefore operates in the background with data collection. Passive biometrics can include:

  • Keystroke dynamics is an analysis of timing, duration, and pressure applied when the individual types on the keyboard. This will create a unique profile of the typing behavior.
  • Behavioral biometrics is an approach involving monitoring several user behaviors including mouse movements, touchscreen interactions, and other usage patterns.
  • Speaker recognition is continuously monitoring an individual’s voice characteristics.


Passive biometrics typically relies on advanced machine learning to analyze and compare data with reference profiles in specific databases. These methods are seamless authentication processes, as they don’t require active actions from the user.

The goal of using both active and passive biometrics is to enhance security along with minimizing access to imposters and fraudsters.

Anycloud Digital Trust enables digital biometrics to fall under the category of behavioral biometrics. The solution creates ID’s which outline various characteristics of the user including behavior and device-linked features. This creates a digital persona of the user. More than 100 different behavior patterns are included such as how users type their passwords, movement of the mouse, geographical location, if the same IP address is used – just to name a few. Anycloud Digital Trust will only allow true users to access their personal information.

Customers on digital platforms expect seamless experiences and Anycloud Digital Trust will ensure safeguarded data from fraudsters.

Gregor Frimodt-Møller

Gregor Frimodt-Møller

Anycloud CEO