Biometric technology for recognition

Nowadays it is more essential than ever to ensure that users feel safe when using a service, a mobile app and when registering on a website. The user’s priority is to know that their data is properly protected. And consequently biometric technology for recognition plays an increasingly crucial role as one of the safest and most efficient ways to authenticate user access to mobile devices, personal email accounts and even online bank accounts.

Biometrics has become one of the fastest, safest and most efficient ways to provide protection to individuals, not only because it is a requirement of authentication for each person as a citizen of a country – considering that fingerprints are some of the data collected and stored for legal purposes and documents – but also because it is the most casual (and reliable) way to protect our cellphones. The advantages of using biometric technology for recognition are efficiency, precision, convenience and scalability.

In IT, biometrics is primarily found connected to identity verification by using a person’s physical or behavioral features – fingerprints, facial recognition, voice recognition and even retina/iris recognition. We are referring to technologies that measure and analyze features of the human body as a way to allow or deny access.

But how does this identification work in the backend? Software that recognises specific points of presented data as starting points. These starting points are then processed and transported to a database which, in turn, uses an algorithm that converts information into a numeric value. It is this value that is compared to a user’s registered biometric entry, the scanner detected and the user’s authentication approved or denied, depending on whether there is a match or not.

The process of recognition can be carried out in two ways: comparing one value to others or comparing one value to another. The process of recognition of one value to others happens when the sample of a user is submitted to a system and compared to samples of other individuals; while the process of authentication of one value to another works with only one user, comparing the provided data to previously submitted data – as with our mobile devices.

There are countless biometric readings, these being some of the most common:

  1. Fingerprinting (one of the most used, economical biometric technologies for recognition, since it has a significant degree of accuracy. In this type of verification, various points of a finger are analysed, such as endings and unique arches). Examples: apps from Médis, MBWay or Revolut;
  2. Facial recognition using a facial image of the user, composed of various identification points on the face, with the ability to define the distance between the eyes and the nose, for example, and the bone structure and lines of each feature of the face. This reading has some percentage of failure, depending on whether the user has a beard or sunglasses. Examples: Apple’s Face ID;
  3. Voice recognition (recognition is carried out from an analysis of the vocal patterns of an individual, adding a combination of physical and behavioral factors). However, it is not of the most reliable method of recognition). Examples: Siri, from Apple, or Alexa, from Amazon;
  4. Retina/iris recognition (being the least used, retina/iris recognition works by storing lines and geometric patterns – in the case of the iris – and with the blood vessels in the eyes – in the case of the retina. Reliability is very high, but so are the costs, which makes this method of recognition less often used). Read this article on identity recognition in the banking industry;
  5. Writing style (behavioural biometrics based on writing style) (lastly, a way to authenticate a user through their writing – for example, a signature – since the pressure on the paper, the speed of the writing and the movements in the air are very difficult to copy. This is one of the oldest authentication tools, used mainly in the banking industry). Read the article on Read API, Microsoft Azure.
Ana LamelasBiometric technology for recognition



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