With the global biometric authentication market projected to reach $187.18 billion by 2031, biometric authentication is a leading innovation in modern security, providing convenience and robust protection in today’s increasingly digital landscape. As cyber threats evolve, biometrics provide a robust solution to verify identities, combat fraud, and enhance user experience. This blog provides a detailed look at how biometric authentication works, highlighting its significance, exploring the different types of biometric systems, and discussing common misconceptions.
How the types of biometric authentication work
Biometric systems rely on unique physical or behavioral characteristics to authenticate an individual's identity. While fingerprint and face recognition are two of the most commonly known biometric methods, technological innovations have led to the rise of other modalities, including voice recognition, iris scanning, and multimodal biometric systems. These alternatives not only deliver enhanced security but also provide flexibility and scalability, often leveraging cloud-based infrastructures to ensure consistency across devices and platforms.
At the core of how biometric authentication works is a biometric template, a secure and encrypted digital representation of a person’s unique traits. During the enrollment process, biometric data is captured—whether it’s a facial scan, a voice sample, or an iris image—and converted into a mathematical format. This template captures the most critical features needed for identification without storing raw biometric data.
Crucially, biometric templates are encrypted and cannot be reverse-engineered to recreate the original data, even if they were to be compromised. They are typically stored in cloud-based environments or decentralized architectures, protected by enterprise-grade security measures such as ISO- and SOC II-certified protocols, mutual authentication (MA), and message-level encryption (MLE). Additionally, rotating encryption keys and strict access controls ensure that only authorized systems and personnel can retrieve or use these templates during the authentication process.
With these protections in place, biometric systems have become increasingly reliable, secure, and scalable across a variety of industries. The following section explores some of the most widely adopted biometric modalities, detailing their operational mechanisms and advantages.
1. Face recognition
Facial recognition technology captures and analyzes distinct facial features, such as the distance between eyes, the shape of the nose, and jawline contours, to create a unique biometric template. These templates are then used to match and authenticate users in real-time.
Operational mechanism:
Facial recognition systems use cameras to capture an image or video of the user’s face. Advanced algorithms then map key facial landmarks such as nose structure and facial contours, to generate a biometric template. During authentication, the system compares the real-time image with the stored template to verify identity. Additionally, passive liveness detection ensures that the face presented is from a real, live person rather than a photo, mask, or AI-generated deepfake. This combination of mapping, comparison, and liveness detection ensures accurate and secure authentication.
Advantages of face recognition:
- Device independence: An enterprise-grade face recognition system, like those offered by Mitek, is not tied to a specific user device. Instead, data is securely stored in the cloud, making it accessible across multiple devices. The solution enables companies to seamlessly integrate biometric capabilities into their existing verification, identity and access management processes.
- Frictionless experience: Passive liveness detection eliminates the need for active participation, reducing user frustration and making it harder for fraudsters to plan for or reverse engineer the necessary actions of an active liveness system.
- Scalability: Easily integrated into mobile apps, enterprise systems, and remote authentication platforms.
2. Voice recognition
Voice recognition captures unique vocal patterns, including pitch, tone, and cadence, to authenticate users. It is particularly useful in voice channels, such as the contact center or in scenarios where hands-free is preferred.
Operational mechanism:
Voice recognition systems rely on microphones to capture a user’s voice, often while speaking a specific passphrase. The system analyzes vocal patterns, including pitch, tone, rhythm, and accent, and converts this data into a biometric template. When a user attempts authentication, their live voice sample is compared against the stored template. To prevent spoofing, these systems often include liveness detection, ensuring that the voice input is live and not pre-recorded. This dual-layer verification enhances both security and reliability.
Advantages of voice recognition:
- Accessibility: Ideal for hands-free authentication, in low or poor light environments, and for users with physical disabilities.
- Cloud integration: Voice templates can be securely stored and accessed across platforms.
- Convenience: Can be used seamlessly in call centers, virtual assistants, and mobile applications.
3. Iris recognition
Iris recognition analyzes the unique patterns in the colored ring around the pupil. This biometric modality is known for its exceptional accuracy and reliability.
Operational mechanism:
Iris recognition systems use specialized cameras to capture a high-resolution image of the user’s iris. The system then maps the intricate and highly detailed patterns in the iris, which are unique to each individual, and creates a biometric template. During authentication, the system compares a real-time scan of the user’s iris with the stored template to verify identity. Due to the precision of iris patterns and the stability of their features over time, this method is highly accurate.
Advantages of iris recognition:
- Uniqueness: Iris patterns are highly unique and remain stable over time.
- Difficult to spoof: Iris are less of a target for advanced fraud like deepfakes.
- Scalability: Effective for high-security environments such as airports and government facilities.
4. Behavioral biometrics
Behavioral biometrics focus on identifying patterns in user behavior, such as typing speed, mouse movements, or even smartphone usage habits.
Operational mechanism:
Behavioral biometric systems operate in the background, continuously collecting data as users interact with devices or systems. Patterns such as typing speed, mouse movement patterns, screen navigation habits, and even the angle at which a device is held are monitored and analyzed. Machine learning algorithms process this data to create a behavioral profile unique to the user. Any anomalies detected in these behavioral patterns can trigger additional verification steps or security alerts, adding a layer of continuous authentication.
Advantages of behavioral biometrics:
- Continuous authentication: Provides ongoing verification during a session.
- Non-intrusive: Operates in the background without interrupting user experience.
- Adaptive: Can detect unusual behavior indicative of fraud attempts
Watch the video below to learn more about how biometric authentication can help your business today:
The evolution to multimodal biometrics
Multimodal biometric systems combine two or more biometric modalities (e.g., facial recognition, voice recognition, or a behavioural trait) to enhance security and accuracy.
Operational mechanism:
Multimodal biometric systems require users to provide data for multiple biometric modalities, such as a facial scan and a voice sample. Each modality is processed independently to create separate biometric templates. During authentication, these templates are compared individually with the live input, and the system generates a match score for each. The final authentication decision is based on a weighted combination of these scores. This redundancy ensures that even if one modality encounters environmental or technical challenges, the other can compensate, enhancing reliability.
Advantages of multimodal biometrics:
- Increased security: Combining multiple modalities makes it significantly harder for fraudsters to bypass authentication.
- Improved accuracy: Reduces false positives and false negatives.
Read our blog post about the advantages and disadvantages of biometrics, to get a complete understanding of the pros and cons of modern biometrics in today’s digital world.
Frequently asked questions about biometric authentication
Despite the clear advantages in security, convenience, and scalability, questions still arise about how biometric authentication works and the level of security it provides. Below, we address some of the most common questions and clarify some misconceptions surrounding biometric authentication.
How is biometric data protected from breaches?
Ensuring data privacy is top of mind for vendors and organizations alike. Some people fear that if a biometric database is breached, their personal data will be permanently compromised, as unlike passwords, biometrics cannot be "reset." It is important to understand that instead of storing raw biometric data, these systems generate biometric templates which are mathematical representations that cannot be reverse-engineered. Moreover, regulatory frameworks such as GDPR and CCPA ensure that organizations handle biometric data transparently, securely, and with user consent. Users must opt-in for biometric enrollment, providing an additional layer of control over their personal information. Additionally cloud-based storage systems are certified by standards like ISO and SOC II, enforcing strict security measures, including mutual authentication (MA) and message-level encryption (MLE).
How accurate and reliable is biometric authentication?
Some users question whether biometric authentication systems can accurately verify identities under varying conditions, such as poor lighting for facial recognition or background noise for voice recognition. While environmental factors can occasionally affect performance, modern systems integrate liveness detection and AI-driven algorithms to reduce false positives and negatives. Some solutions take a multimodal approach – for instance offering both face and voice – to account for scenarios where one score may be low due to conditions. Combining two or more authentication methods (e.g., face and voice), significantly improves accuracy and reliability, even in challenging scenarios.
How do biometric systems prevent spoofing and deepfake attacks?
A common question surrounding biometric systems is how to combat spoofing attempts using photos, voice recordings, or deepfake technology. While early biometric systems were susceptible to such attacks, advancements in liveness detection have significantly strengthened their defenses. Passive liveness detection, in particular, can seamlessly verify whether the presented face or voice belongs to a live person or is an imitation such as a printed photo, mask, or digital image being shown to the camera.
Additionally, AI-powered algorithms analyze subtle details and anomalies that might indicate fraudulent activity. By combining liveness detection with advanced AI analysis, modern biometric systems have become highly resilient against spoofing attempts and injection attacks, offering robust protection against increasingly sophisticated forgery techniques.
How do biometric authentication systems address bias?
Ethical concerns in biometric authentication often stem from biases that may arise in systems when factors such as skin tone, age, or voice accent affect accuracy. Historically, these biases have been linked to poorly trained algorithms and limited datasets. However, modern biometric systems have made significant progress by using diverse and representative training datasets to minimize inaccuracies.
Additionally, multimodal biometric systems, which combine multiple authentication methods like facial and voice recognition, help address the limitations of single-modality systems, creating a more inclusive and reliable approach. Vendors also have model governance policies in place to ensure their systems are trained on non-biased datasets, improving accuracy and fairness across diverse populations.
Takeaways on how biometric authentication works
Biometric authentication stands at the forefront of modern security, offering a seamless blend of convenience, accuracy, and robust protection. From facial and voice recognition to advanced multimodal systems, biometric technologies are reshaping how individuals and organizations approach identity verification. By addressing concerns around privacy, data security, and inclusivity, these systems continue to evolve, becoming more secure, scalable, and user-friendly.
As cyber threats grow more sophisticated, adopting biometric authentication isn't just an option—it's a necessity. Organizations that prioritize secure and frictionless authentication solutions are better equipped to protect user data, reduce fraud, and build long-lasting trust with their customers.
Want to dive deeper into how multimodal biometric authentication can help your organization combat fraud and enhance user experiences?
Download our comprehensive guide -- Fight fraud with multimodal biometric authentication
About Becky Kiichle-Gross
Becky Kiichle-Gross is Principal Software Product Manager at Mitek, where she leads the development of the company’s image capture and multimodal biometric authentication solutions. Becky has a deep understanding in product development and has managed several product launches across markets including retail, healthcare, aerospace, and banking. With extensive expertise and a passion for solving customer problems, Becky is instrumental in driving innovations that help clients combat fraud and bolster trust.