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Written by: Laura Fitzgerald

Head of Brand and Digital Experience

Biometric authentication was once the most robust security measure. It used hard-to-impersonate biological traits like fingerprints to verify identity. However, nowadays, biometric authentication is not all secure. Fraudsters can bypass the authentication with 3D-printed masks, fake fingerprints, and eye replicas.

Biometric liveness detection helps seal the vulnerability of traditional biometric authentication. This security algorithm uses biometric data coupled with physiological responses like blinking to catch fraudsters.

What is Biometric Liveness Detection?

Biometric liveness detection verifies whether a biometric sample is from a live human. This security system has one principal purpose — it prevents the use of fake biometrics to impersonate or commit fraud.

Biometric liveness detection uses several cues to establish liveness; these include physiological responses like blinking and smiling. Moreover, this security system can use other cues like voice and skin texture to catch fraudsters. 

Like any security system, biometric liveness detection can be used across various sectors. Airports, financial institutions, and insurance providers can use it to enhance security. Moreover, border control and e-commerce facilities can use biometric liveness.

How Liveness Detection Works and Prevents Fraud

Biometric liveness detection uses a combination of technologies to unequivocally verify that the biometric data being presented originates from a live human being. Some of these technologies include:

1. Motion Analysis

Motion analysis is one of the technologies used in biometric liveness detection. This security algorithm analyzes various natural movements to establish liveness. For instance, in facial recognition, biometric liveness technology checks for various facial movements. 

These include blinking, smiling, or nodding the head. The advanced security measure can also use eye trackers to observe gaze direction. Images or videos used in impersonation cannot replicate these facial movements.

2. 3D Depth Sensing

3D depth sensing is another technology used in biometric liveness detection. 3D depth sensing uses technologies like time-of-flight cameras and laser scanners to determine whether a face is alive.

In particular, the 3D depth sensing technology uses facial shape to determine liveness. Moreover, 3D depth sensing can use the distance between the eyes and nose or lip curvature to establish if an individual is alive. 

3. Texture Analysis

Texture analysis is another method used to verify the liveliness of individuals. In this technique, a biometric system scrutinizes the unique patterns of an iris, face scan, or fingerprint. The patterns include fingerprint ridges valleys and iris crypts.

The characteristics mentioned above are inherent to a living person and absent in impersonation replicas. The biometric liveness detection system compares the results with expected properties to establish liveness.

4. Challenge-Response Tests

Some biometric liveness detection systems incorporate challenge responses to check for liveness. In this approach, the system prompts the user to perform specific requests that require real-time human reactions.

For instance, during facial verification, the biometric security systems might ask the subject to blink. Moreover, these advanced security algorithms can request an individual to nod or smile. Non-human entities cannot outmaneuver random requests.

Besides the actions, a biometric liveness detection system can request an answer to a question. The biometric detection systems use voice authentication to ascertain if the voice is from a live person.

5. Machine Learning

Machine learning is another technology that plays a pivotal role in biometric liveness. Security experts train ML models to spot signs of liveness in biometric samples. Some cues machine learning uses to authenticate a live sample include:

  • Blinking
  • Eyebrow movements
  • Pulse rate
  • Skin elasticity
  • Skin temperature
  • Voice

For instance, in facial detection, ML algorithms use color, texture, or blinking to determine liveness. Likewise, in the case of fingerprints, ML systems can analyze things like ridge quality and sweat pores to assess if a sample is live.

Machine learning algorithms can combine various authentication modalities to thwart spoofing. Advanced models can use voice, fingerprint, iris, and facial detection to cut the chances of impersonations. 

Types of Liveness Detection

Typically, biometric systems use two types of liveness detection — passive and active. Each type of liveness detection uses a different approach to catch fraudsters. The following is an overview of how each liveness detection method operates:

Passive Liveness Detection

Passive liveness detection determines liveness without prompting any action from the subject. These biometric systems use AI to look for common signs of biometric spoofing, including photos, videos, or masks.

Besides, passive liveness detection systems can check for signs of liveness to authenticate biometrics. For instance, the biometric system can use skin texture to verify if a sample is live. In addition to texture, passive liveness detection checks for liveness using the following aspects:

  • Color. Passive liveness detection compares the subject’s color to a reference to spot inconsistencies.
  • Depth. Besides color, passive liveness detection can assess the contours of the eyes, mouth, and nose to establish liveness.
  • Motion. Passive liveness detection systems can monitor natural facial motion patterns. These motion patterns occur when breathing, blinking, or talking.

Active Liveness Detection

Unlike passive detection, active liveness detection prompts users to perform specific actions during identity verification. In particular, the system issues random instructions to make it harder for fraudsters to bypass.

Some of the most common requests used in active liveness detection include:

  • Blinking. An active liveness detection system instructs users to blink when prompted. Afterward, the biometric system monitors for real-time eye movement to confirm liveness.
  • Facial gestures. Besides blinking, an active biometric system can prompt users to smile or nod during verification. Again, the biometric system monitors real-time facial expressions to verify liveness.
  • Voice commands. Sometimes, the active liveness biometric systems can ask the user to say specific phrases. Afterward, the system analyzes the voice inflections to ascertain if the voice is natural.

The Benefits of Liveness Detection for Contact Centers

Biometric liveness detection can be used across multiple industries. However, this security advancement has proven more valuable in contact center security. It ensures that only live and authorized individuals have access to sensitive customer information.

Apart from preventing unauthorized access, biometric liveness detection can offer the following benefits:

1. Reduced Risk of Data Breaches

Data breaches are rampant in contact centers using less sophisticated security measures. The breaches occur when fraudsters impersonate legitimate customers. In that event, agents disclose sensitive information unknowingly.

Biometric liveness detection can help eliminate these data breaches. The security algorithms use advanced authentication modalities like voice commands to stop impersonation. With this security system, contact centers can keep violations to a minimum.

2. Secured Self-Service

Self-service is a growing trend in customer support. This model allows customers to resolve issues independently, leading to shorter wait times and improved satisfaction. Furthermore, self-service frees up the hands of support staff.

Biometric liveness helps make self-service more secure. The algorithms verify the liveliness of users, ensuring that only authorized people get access to a customer account. This advanced security protects customers from fraudulent activities.

3. Lower Operational Costs

Investing in biometric liveness detection can help reduce a contact center’s running costs in many ways. For one, biometric liveness, especially voice authentication, reduces the need for manual identity validation. The automatic verification minimizes the need for live agents to verify identity.

Furthermore, biometric liveness reduces operational costs by blocking fraudulent activities. With the reduced exposure to fraud, entities won’t spend on reputation repair, compensation, and legal expenses.

4. Improved Customer Trust

Biometric liveness doesn’t just keep fraudsters off a contact center. This security measure can also help foster customer trust. The standard assures customers that a service provider treats their data with the utmost care.

As a result, the customers will trust the organization with their sensitive information. Moreover, biometric liveness reduces data breaches, an issue that could erode trust. Beyond trust, biometric liveness enhances loyalty, reduces churn, and boosts reputation.

5. Improved Compliance

Biometric liveness detection is a valuable tool in compliance. It enables contact centers to adhere to strict industry regulations set by various authorities like the Data Protection Act.

This advanced security measure helps verify the identity of clients before disclosing sensitive information. As a result, it protects support agents from revealing private information to impersonators.

The enhanced compliance doesn’t just save organizations from costly fines and legal expenses. It also helps the entities maintain a positive public image, which is crucial in the competitive business sphere.

6. Expedited Customer Verification

Biometric liveness does not only provide a higher level of security, but it also expedites the verification process. The algorithms used in this security technology can verify liveness in just a few seconds.

The expedited customer verification comes along with many benefits. It eliminates cumbersome and time-consuming knowledge-based questions, helping save time. Support agents can use the saved time on other profit-making business processes.

Use Pindrop to Improve Contact Center Security

Enhancing call center security doesn’t end after acquainting with disruptive security measures. But, you require the support of a service provider with a deep understanding of the intricate security requirements in this domain.

Our company, Pindrop, is one such partner in matters of contact center security. We use voice to fortify the authentication process so you keep fraudulent access bay. 

Request a demo to learn how we can help improve your contact center security.