https://www.techtarget.com/searchsecurity/definition/biometric-authentication
Biometric authentication is a security process that relies on the unique biological characteristics of individuals to verify their identity. Instead of relying on personal identification numbers (PINs) or passwords, biometric authentication systems compare physical or behavioral traits to stored, confirmed, authentic data in a database. If both samples of the biometric data match, authentication is confirmed. Typically, biometric authentication is used to manage access to physical and digital resources, such as buildings, rooms and computing devices.
Biometric identification uses biometrics, such as fingerprints, facial recognition and retina scans, to identify a person, whereas biometric authentication is the use of biometrics to verify that people are who they claim to be.
The following examples of biometric technology built using computer vision algorithms. These technologies can be used to digitally identify people or permit them to access a system:
A biometric device includes three components: a reader or scanning device, technology used to convert and compare collected biometric data, and a database for storage.
A sensor is a device that measures and captures biometric data. For example, it could be a fingerprint reader, voice analyzer or retina scanner. These devices collect data to compare to the stored information for a match. The software processes the biometric data and compares it to match points in the stored data.
Most biometric data is stored in a database that's tied to a central server on which all data is housed. However, another method of storing biometric data is cryptographically hashing it to enable the authentication process to be completed without direct access to the data.
Many advanced systems use multimodal biometrics, combining two or more biometric methods, such as fingerprint and facial recognition, to enhance security and accuracy, making it significantly harder for unauthorized individuals to gain access. Multimodal biometric authentication adds layers to an authentication process by requiring multiple identifiers, which are read simultaneously during the process.
Multimodal biometrics can be considered a form of multifactor authentication (MFA). However, it differs significantly from the more commonly understood form of MFA, where users typically input sensitive information, such as a password and a one-time code, into a mobile or desktop device.
Multimodal biometric authentication is often used in high-security environments such as data centers, government facilities, banking systems or any place where the cost of identity compromise is high.
Increased security without the need for key cards, access cards, passwords or PINs is among the advantages for organizations that choose to adopt this approach. Additionally, malicious actors who attempt to hack or fake their way through an authentication system have a harder time faking two or more unique characteristics of an individual than if they were to try faking only one.
However, this approach also comes with a few disadvantages. High costs can be incurred when assembling and implementing the tools needed, such as scanners, computing power and storage space for biometric data. Also, use of this technology can intensify public perception that an organization is collecting and storing personal information unnecessarily, which can then be used to surveil people with or without their consent.
Examples of areas where biometric authentication is used include the following:
Law enforcement and state and federal agencies use different kinds of biometric data for identification purposes. These include fingerprints, facial features, iris patterns, voice samples and DNA.
For example, the Automated Fingerprint Identification System (AFIS) is a database that is used to identify fingerprints. It was first used in the early 1970s as a way for police departments to automate their otherwise manual fingerprint identification process, making it quicker and more effective. In the past, a trained human examiner had to compare a fingerprint image to the prints on file. If there was a match, the examiner would double-check the two prints to verify the match.
Today, AFIS can match a fingerprint against a database of millions of prints in a matter of minutes.
An electronic passport or e-passport is the same size as a conventional passport and contains a microchip that stores the same biometric information as a conventional passport, including a digital photograph of the holder. A chip stores a digital image of the passport holder's photo, which is linked to the owner's name and other personally identifiable information.
The e-passport is issued electronically by a country's issuing authority, which checks the identity of the applicant. They use fingerprints or other biometric information to confirm that the data in the chip matches the information provided by the applicant before issuing the passport.
Hospitals use biometrics to more accurately track patients and prevent mix-ups. Clinics and doctors' offices use it to keep patients' information secure. Using biometric data, hospitals can create digital identities of patients that help them store and access those patients' medical histories. This information can be used to ensure the right patient gets the right care, whether that means faster identification in emergencies or preventing medical errors.
An identity and access management (IAM) system is a combination of policies and technology tools that collectively form a centralized means of controlling user access to important information a business has stored.
IAM systems use methods such as single sign-on, two-factor authentication and MFA. They also use sophisticated tools, including biometrics, analysis of behavioral characteristics, AI and machine learning, as part of their overall strategy to make authentication more rigorous and secure.
The use of biometric authentication in payments and credit card processing is nascent and slowly expanding. The idea is to add more security to payments without added complexities or frustrations. Examples of biometric payments have consumers using cards to pay for goods, but those transactions are only authorized after they scan their fingerprint, eye or face.
There's more than one way to scan as well, since cards can have built-in sensors to scan fingerprints, while a register or kiosk might have scanners readily available.
Biometric authentication plays a growing role in the education sector, offering enhanced security and streamlined operations. For example, it's used for student identification, ensuring accurate attendance tracking and providing secure access to school facilities.
Biometric authentication also helps prevent impersonation during exams by verifying that the test-taker is the enrolled student. It can also enable secure library access and contactless checkout of resources for students.
Biometric authentication is becoming increasingly integrated into everyday living through smart home systems and connected vehicles. In modern homes, facial or voice recognition can be used to unlock doors, disarm security systems, adjust lighting and climate settings, and interact with digital assistants. This adds convenience and an extra layer of security by ensuring that only authorized users can control key functions.
In the automotive industry, several manufacturers are incorporating biometrics into vehicles. For example, a fingerprint or facial recognition is used to start the car, unlock doors and personalize driver settings, such as seat position, mirror angles and infotainment preferences.
Biometric authentication significantly enhances physical access control, securing premises and ensuring only authorized individuals can enter restricted areas. This is achieved through various methods, such as fingerprints, facial recognition, or iris scans to grant entry to buildings, sensitive server rooms, or specific zones within a larger facility.
Additionally, it streamlines time and attendance tracking by enabling employees to clock in and out with their unique biometrics, helping prevent time theft and ensuring accurate payroll records.
Biometric authentication offers both advantages and disadvantages.
In the United States alone, business use of biometric authentication has drastically increased in recent years as more business leaders are becoming confident in its capabilities. Here are the key advantages of biometric authentication:
While biometrics offers many advantages for particular industries, there are controversies surrounding its usage. Here are the key issues related to biometric authentication:
Biometric authentication and passwords are both methods of proving identity, but they work in different ways, each with its strengths and trade-offs. The following is a comparison of various aspects of both methods:
Biometric authentication uses unique physical or behavioral traits, such as fingerprints, face or voice, to verify a person's identity. On the other hand, passwords are secret words or phrases that users input to confirm their identity.
Biometric authentication typically offers stronger protection than traditional passwords because the traits used for identification are inherently difficult to replicate, guess or phish. It also resists brute-force attacks that commonly target passwords. However, biometric systems aren't foolproof and can be spoofed using techniques such as fake fingerprints, high-resolution photo masks, or 3D-printed replicas.
Whereas the security of passwords largely depends on their complexity and uniqueness. Weak or reused passwords are especially vulnerable to security breaches and are linked to poor password practices. Passwords are also easily compromised through phishing, brute-force attacks or even physical methods such as thermal or smudge analysis.
Once compromised, biometric data can't be reset, posing a significant challenge. Additionally, environmental factors or physical changes can affect the accuracy of biometric systems. However, passwords can be changed immediately if compromised, unlike biometric data. The flexibility of passwords enables users to quickly mitigate security risks.
Biometric authentication is quick and effortless, requiring only a simple presentation of a finger or face, with no need to type anything. This streamlined process enhances user convenience and helps eliminate password fatigue that comes from managing numerous credentials across different platforms.
Passwords remain a familiar and universally accepted method of authentication, requiring no specialized hardware to set up. However, they can be frustrating for users to manage, as they're often difficult to remember and frequently forgotten, especially when strong, unique passwords are used for multiple accounts.
Biometric authentication requires specialized hardware and software, leading to higher initial setup costs. Ongoing maintenance and system updates also add to the expenses. Additionally, organizations must ensure compliance with data protection regulations when handling biometric data.
Passwords don't require specialized hardware for implementation, making them cost-effective and easy to deploy. However, managing passwords across multiple platforms can be cumbersome and prone to human error.
To address the limitations of both methods, many modern security systems integrate biometric authentication with passwords, such as using a fingerprint to unlock a password manager. This hybrid approach uses the strengths of both methods, offering a more secure and user-friendly authentication experience.
While biometric authentication systems are generally more secure than traditional passwords, they aren't immune to sophisticated attacks. However, no technology is entirely hacker-proof. The following is a breakdown of how biometric authentication can be hacked or bypassed:
The future of biometric authentication is expected to be characterized by increasing sophistication, deeper integration into daily life, and a continuous push towards enhanced security and user convenience. Several key trends and advancements that are shaping this evolution include the following:
AI and machine learning are playing an increasingly central role in advancing biometric authentication systems. These technologies enhance accuracy, adapt to changing user traits and help defend against sophisticated spoofing attempts, such as deepfakes. They do this by analyzing micro-expressions, voice intonation and behavioral patterns. For example, modern facial recognition systems now use deep learning to detect subtle facial movements and 3D depth, making them more resilient to photo or mask-based spoofing.
According to a Gartner press release, by 2026, 30% of enterprises will consider identity verification and authentication tools unreliable when used in isolation, due to the growing threat of AI-generated deepfakes. This highlights the growing need for layered security approaches and technologies such as liveness detection.
Voice authentication with AI is also becoming stronger. For example, AI models can analyze pitch, cadence and even unnatural pauses in speech to detect deepfake audio with increasing precision.
The future of biometric authentication is rapidly advancing toward multimodal systems that integrate two or more distinct biometric modalities, such as facial recognition, fingerprint scanning and voice authentication. This layered approach enhances security, making it much more difficult for attackers to spoof multiple traits at once. It also improves reliability and accessibility by offering users multiple options for identity verification.
There is also a strong shift toward contactless biometrics, driven by growing demands for convenience and heightened hygiene concerns, especially in the wake of recent global health events. Innovations in this area include advanced facial recognition, precise iris scanning and hover-based technologies for palm or fingerprint authentication, all designed to eliminate the need for physical contact during the verification process.
Beyond physical traits, behavioral biometrics, such as typing rhythm, mouse movements, gait and voice patterns, are seeing increased adoption. These systems work passively and continuously, verifying a user's identity in the background as they interact with a device or system. This enables real-time identity assurance by detecting anomalies that might signal session hijacking or insider threats, enabling adaptive security responses based on deviations from the user's typical behavior.
Biometric data is increasingly being processed locally on edge devices, such as smartphones and smartcards, reducing the need to transmit sensitive data to the cloud. This enhances both speed and privacy, especially in areas with limited connectivity.
At the same time, technologies such as blockchain are being explored as a way to store immutable, verifiable biometric credentials. This could give individuals greater control over their data, enabling them to share it securely without relying on centralized third-party systems.
Explore the most common digital authentication methods and discover how they play a vital role in enhancing cybersecurity for both organizations and users.
18 Jul 2025