These days, we may use our fingerprint, voice, or face to unlock our phones. Our bank even uses a thumb scan to confirm transfers worth millions of dollars. However, for some reason, many crucial accounts continue to use outdated credentials, which can be as weak as "Password123!" The Verizon DBIR reports that 88% of 2024 attacks against simple web apps used credentials that had been stolen, underscoring the urgent need to move past antiquated authentication techniques.
Here comes biometric authentication, which is rapidly taking the lead in user authentication as it recognizes people by their identity rather than their knowledge. In 2022, 72% of people worldwide chose face verification for safe online transactions, and in 2024, over 50% of all users authenticated every day using biometrics.
However, is biometric authentication truly that safe, and how does it operate? Let's determine whether this authentication technique is appropriate for your program, website, or app.
What is Biometric Authentication?
A cybersecurity procedure known as "biometric authentication" uses a user's distinct biological characteristics, such as their fingerprints, voice, retina, and facial features, to confirm their identity. When a user enters their account, biometric authentication systems use the information they have stored to confirm their identity. Generally speaking, this kind of authentication is more secure than more conventional multi-factor authentication methods.
Types of Authentication Methods
Some of the biometric authentication technologies below are ones you may use on a regular basis, and the following are some popular authentication techniques used for network security intended to defeat hackers.
Facial recognition: These technologies recognize individuals based on their distinctive facial traits. It is utilized in many different contexts, including police enforcement, credit card payments, and smartphones.
Fingerprint Recognition: Using a device such as a FIDO2 Authentication Token, fingerprint authentication utilizes an individual's distinct fingerprint to confirm their identity. It is the most used biometric authentication method and can be used to secure anything, including buildings, cars, and mobile devices.
Eye Recognition: Eye recognition identifies a person by using their distinct iris or retinal pattern. Compared to other biometric authentication alternatives, this one is less popular since it is more difficult to install. To assure accuracy, an iris scan needs a camera that can see infrared light source and no light pollution.
Voice Recognition: To authenticate a person, voice recognition utilizes their distinct tone, pitch, and frequencies. When a user contacts a call center for customer service support (like online banking), this biometric is most frequently utilized to confirm their identity.
Retina/Iris Recognition: Retina, sometimes called iris recognition, recognizes a person by their retinal or iris pattern. Because it is more difficult to install, this kind of biometric authentication is less widespread.
Gait Recognition: This technique verifies an individual's identity by observing how they walk. The way a person puts one foot in front of the other is a good approach to confirm their identification because everyone walks a bit differently.
How Biometric Authentication Works?
The process of a fingerprint scan on a smartphone, from the time the user initially sets it up to each daily unlock, will help us understand how biometric authentication protects the user's digital identity.
Core components
Three key elements must cooperate for biometric systems to function:
- Capacitive scanners for fingerprints, infrared cameras for faces, and microphones for speech are examples of sensors that gather biological data from users.
- Storage: Safely saves the user's biometric pattern locally on their device or in secured databases.
- Processor: Uses advanced matching algorithms to compare fresh scans with previously stored templates.
Raw data vs. templates
The system does not save a raw image of the fingerprint when the user initially registers it. Rather, it extracts distinctive features, such as spatial connections, minutiae points (where the ridge lines branch or terminate), and ridge patterns. These patterns are transformed into a mathematical model, which is usually kept in a safe location as 1-2 kilobytes of encrypted data. The high-resolution fingerprint picture, which is their genuine biometric data, is taken, analyzed, and then promptly thrown away. For future comparison, just the mathematical representation—also referred to as a template—is retained.
Significant information is lost throughout the one-way transformations and feature extraction steps of the template building process. Rebuilding a fingerprint picture from a template is not physically impossible, but it is computationally challenging due to data gaps. In the meanwhile, there is just no longer the pixel-level detail required to replicate real ridge patterns.
On-device vs. server-side storage
The next step after creating the biometric template is deciding where to keep it. On-device storage is becoming more and more popular in modern systems, where the template remains on the user's device within a trusted execution environment (TEE) or secure enclave. By keeping biometric information close to the hardware, this configuration lowers the possibility of interception or widespread data breaches.
On the other hand, server-side storage entails sending the biometric template to a centralized database so that it may be stored and compared. This method makes a high-value target even though it can make enterprise-wide administration or multi-device authentication easier. Many users' biometric templates—data that, in contrast to passwords, cannot be altered—could be exposed simultaneously in a breach.
On-device storage has becoming the norm for consumer electronics like laptops and smartphones since it is more in line with privacy-by-design principles. By keeping matching activities local to the device, it facilitates speedier authentication, lessens network dependence, and makes spoofing efforts much more difficult. For this reason, on-device processing is the foundation of technologies like Android's BiometricPrompt API and Apple's Touch ID and Face ID.
Is It Actually Safe?
To improve security, biometric authentication—such as fingerprints, retinal scans, and facial IDs—was added to our devices. Nonetheless, biometric hacking has grown in popularity as a means for thieves to get private information in recent years. Hackers can obtain sensitive data by employing specialized tools and tactics to get over conventional security measures like passwords and personal identification number (PIN) codes.
Can biometric data be hacked?
No security measure, including biometric data, is infallible. Although biometric information is safer than other types of identification, such a password or PIN, skilled hackers can still get past biometric security measures.
Even while biometric information is vulnerable to hacking, it is still safer than other types of identification. This is due to the fact that forging an iris or fingerprint is far more difficult than figuring out a password or PIN.
Furthermore, biometric information is frequently combined with additional identifiers, such a password or PIN, to further complicate system access for hackers.
How Do Biometrics get hacked?
Biometrics may be hacked in a number distinct ways. Using a tool known as a skimmer is one popular technique. ATMs and other fingerprint scanning devices can be equipped with this gadget. After gathering data from the finger scan, the skimmer generates a phony fingerprint that may be used to unlock the device.
Spoofing is another kind of biometric hacking. This method is creating a phony fingerprint or iris that closely resembles the actual one in order to trick the scanner. This assault can be carried out by creating a mold of the victim's finger or by taking a photo of their iris.
The so-called "replay attack" is another method of compromising biometric data. Here, a hacker captures an authorized user's biometric information, which they may then replay to enter the system.
The employment of a skimmer by a gang of hackers to gather the fingerprints of more than a
million individuals is among the most well-known instances of biometric hacking. They then
gained access to private data, including government documents and bank accounts, using these
fingerprints.
As technology becomes more widely used, biometric hacking is becoming
increasingly frequent.
Understanding how biometrics might be compromised and taking precautions to safeguard your personal data are crucial.
Conclusion
Biometric authentication is not invulnerable, but it remains more secure than traditional identifiers like passwords. The key lies in layered security: pairing biometrics with PINs, passwords, or behavioral checks to reduce risks.
As technology advances, both users and organizations must stay informed about evolving threats and adopt privacy-by-design principles—ensuring biometrics remain a trusted safeguard rather than a vulnerability.