Types of Biometric Authentication

Biometric authentication refers to verifying a user’s identity using their unique biological traits.

This form of authentication is considered more secure than traditional methods, as biometric traits are almost impossible to replicate. There are various types of biometric authentication methods, each having its advantages and limitations.

In this blog, we give you an overview of the types of biometric authentication techniques used today.

Physiological vs Behavioural Biometrics

Biometric authentication techniques can be divided into two main categories:

Physiological Biometrics: These authenticate users using measurements related to the human body, such as fingerprints, iris/retina scans, facial recognition, DNA matching, etc. Since these biometrics are linked to unique physical traits, they form the basis of most biometric systems today.
Behavioural Biometrics: These biometrics authenticate users based on measurements related to human behaviours such as voice recognition, keystroke dynamics, gait analysis, etc. They utilise pattern recognition techniques to identify consistency as well as variation in human activities.

Common Physiological Biometric Techniques

Following are some of the well-known physiological biometric techniques:

Fingerprint Recognition

One of the most common types of biometric authentication, fingerprint recognition, analyses the unique patterns found on human fingertips.

Small differences, even between fingerprints of identical twins, allow fingerprint scanning systems to differentiate between various users. Fingerprint authentication is inexpensive, user-friendly, and highly accurate.

Iris Recognition

The Iris recognition technique uses the visually distinct patterns of the coloured ring-shaped membrane surrounding the pupil to identify users.

Iris patterns contain many unique features, such as furrows, ridges, etc., and provide immense variation even between identical twins. Iris scanners use high-quality cameras and infrared illumination to capture the intricate iris textures precisely.

Facial Recognition

Facial recognition systems measure facial characteristics such as the distance between eyes, width of the nose, shape of cheekbones, etc., to create a faceprint.

Sophisticated algorithms map key facial points and match faceprints to images stored in a database. Many smartphone manufacturers now use basic facial recognition capabilities for device unlock authentication.

Vein Recognition

Vein recognition scans the vein patterns underneath the skin using near-infrared light. As haemoglobin in the blood absorbs infrared light, the vein pattern appears as a dark shadow.

The vein patterns in the back of the hand, wrist, or fingers provide distinguishable features for biometric mapping. Vein recognition offers higher accuracy than fingerprint scanning.

Common Behavioural Biometric Techniques

Voice Recognition

One of the most convenient biometric authentication techniques, voice recognition, verifies users by analysing their vocal tone, pitch, and physical manner of speaking.

The distinctiveness of an individual’s voice arises from differences in vocal tracts, mouth movements, and nasal tones. Banks frequently use voice biometrics when interacting with customers over the phone.

Signature Recognition

Signature recognition techniques can perform verification statically by comparing a sample signature with reference data or dynamically by monitoring signature drawing patterns, speed, etc.

Dynamic recognition offers better accuracy, as signatures drawn slower or faster than normal can indicate attempted forgery. Static verification is generally used for document signing, while dynamic is common for access control systems.

Keystroke Recognition

Keystroke recognition focuses on the typing rhythm and speed to profile users. Small timing differences exist between users due to varied hand sizes, typing techniques, and individual perceptual motor skills.

By monitoring the timing between essential keyboard events, keystroke dynamics solutions provide continuous user authentication.

Gait Recognition

Gait recognition analyses several aspects of the identifiable pattern corresponding to how a person walks or runs.

Physical traits such as step length, walking speed, limb movement, posture, balance, and foot pressure provide key distinguishing input that enables gait analysis systems to verify user identity.

Highly sophisticated pressure sensor floor panels measure foot shape, toe position, and step cadence data to facilitate the extraction of gait biometrics. Radar-based motion detectors are also being developed to capture these distinct characteristics remotely.

Multimodal Biometric Authentication Systems

Many biometric authentication systems now combine inputs from multiple biometric modes to offer greater reliability. For instance, airport security might use facial recognition and iris scan data to verify passenger identity conclusively. Using two or more unrelated biometric inputs makes spoofing exponentially harder, even if one set of biometric data is compromised.

Most multimodal systems implement biometric fusion at the matching score level. For example, fingerprint and iris scanners provide an individual matching score indicating how closely input data matches the enrollment data. A fusion algorithm then combines these scores using methods like weighting to make an optimised accept/reject decision.

Benefits and Limitations of Biometrics

Biometric authentication offers convenience coupled with stronger security against many external attacks aimed at stealing user login credentials or hacking accounts using stolen passwords.

However, biometrics also come with some technological and societal limitations that must be addressed through appropriate policy safeguards:

Pros

Extremely difficult to forge or imitate inherent biometric traits, making attacks harder.
Eliminates the risk of losing access cards or forgetting passwords.
Continuously available for transparent user authentication.

Cons

Mandatory, strong encryption is essential when templates are stored to prevent data misuse.
Social issues concerning user privacy that need equitable policy solutions.

The choice of which biometric technique works best depends on the access environment and security policies of the organisation. Proper safeguards must exist before collecting and storing sensitive user information.

Implemented correctly, biometric authentication enhances system security manifold while facilitating ease of use.

Conclusion

Modern biometric systems offer varied options to verify user identity accurately for controlled access management across industrial and governmental organisations.

Multimodal biometric fusion architectures, in particular, deliver very high accuracy rates - promising continued innovation and widespread global adoption of biometric user authorisation and authentication.

Using multi-factor authentication (MFA) with biometrics provides an added layer of security. For easy-to-implement and robust MFA, ensure to leverage authentication solutions with Instasafe.

FAQs

What is the most common type of biometrics?

The most common biometric security measures are fingerprint and iris scanning. Facial and finger/palm vein pattern identification are also growing in popularity.

What is the best type of biometrics?

Biometric identification using iris recognition is considered the most accurate. The technology comprises image capture, compliance check, image enhancement, compression, and biometric template development for matching.

What is biometrics and its types?