Liveness detection is a technique for verifying the real-time presence of online identities. It involves the use of algorithms that analyse biometric traits to determine if their source is a live human being or a spoofed representation.

Importance in fraud prevention

Liveness detection is crucial to prevent fraudulent identity attempts by verifying the live presence of an individual. This counters spoofing attacks that involve the use of fake biometric samples to gain unauthorised access.

Without this mechanism, attackers can easily cheat biometric systems using masks or high-resolution pictures or videos of the genuine user’s face.

Types of liveness detection

Liveness detection mechanisms can be categorised into three types:

• Active: Requires the user to perform certain actions, such as blinking, nodding or smiling to prove real-time presence.

• Passive: Analyses a biometric trait’s inherent characteristics, such as blood flow, pulse or thermal properties to detect signs of liveness using artificial intelligence (AI).

• Hybrid liveness model: Combines both active and passive liveness detection methods to maximise accuracy.

How does it work?

Liveness detection relies on the subject’s movements, texture and other dynamic features. It tracks and assesses various characteristics, including facial and hand movements, to determine if the biometric trait belongs to a live individual.

For example, a liveness detection system may ask the subject to blink or nod their head. Real users exhibit natural movements that the system can track and verify.

Technologies and methods

Liveness detection utilises a variety of technologies, including motion tracking, texture analysis, 3D depth sensing and AI and machine learning algorithms.

These are the tools and systems used to execute liveness detection:

Facial analysis

Facial movements, texture and depth are analysed to verify liveness. The system may track blinking or ask the user to perform a specific action, such as smiling, to distinguish real-time presence from static images. It can also utilise 3D depth sensing to create a representation of the subject’s face and detect depth and movement.

Voice biometrics

Analyses the subject’s vocal patterns, tracking pitch, tone and rhythm to determine liveness. The system might prompt the subject to say specific phrases or words.

Fingerprint scans

Assesses blood flow or sweat patterns during fingerprint scans to detect signs of liveness. The subject might be instructed to press hard or slightly move their finger during scanning.

Iris recognition

Tracks eye movement, pupil dilation and texture to verify liveness. This mechanism is often combined with specific actions, such as looking left or right.

Benefits of liveness detection

Liveness detection offers many benefits, including:

• Enhancing security: Prevents presentation attacks and identity theft by ensuring that only live individuals can validate their identity, essentially fraud-proofing biometric verification.

• Streamlining identity verification: Enhances identity verification via instant identity checks, removing the need to prepare and verify physical documents.

• Enhancing user experience: Offers a seamless and convenient authentication process via active, passive and hybrid approaches.

• Upholding privacy and compliance: Enables organisations to adhere to strict regulatory requirements for authentication and fraud prevention while minimising data breaches.

Use cases

Here are the core applications of liveness detection:

• Banking and finance: Secures customer onboarding and authentication for online banking and financial transactions.

• Strengthening KYC processes: Increases the accuracy and reliability of Know Your Customer (KYC) processes by verifying the subject’s physical presence.

• Border control and immigration: Enhances security at border checkpoints by verifying the liveness of individuals during passport and visa authentication.

• Access control: Secures physical access to facilities by pairing with biometric authentication.

• Healthcare: Ensures the integrity of patient identification and enhances the security of electronic health records.

*Disclaimer: This content does not constitute legal advice. The suitability, enforceability or admissibility of electronic documents will likely depend on many factors such as the country or state where you operate, the country or state where the electronic document will be distributed as well as the type of electronic document involved. Appropriate legal counsel should be consulted to analyze any potential legal implications and questions related to the use of electronic documents.