The Most Secure and Accurate Biometric Modality: A comparative analysis

During my identity management consulting sessions, I come across all different sorts of questions about biometric systems. People from different background, industry verticals, totally non-technical to highly tech savvy individuals come up with their queries. Even people who have technical background and some understanding of biometric systems, seem confuse when they look at the available options. When budget is the criteria, people might want to go for low-cost options; however, things go complicated when they need “the best”, “most secure” or “most accurate” biometric modality.

In this article, we will try to figure out which modality can be called “the most secure and accurate biometric modality” by discussing all popular options. It will include overview and comparison of popular biometric approaches, specially emphasizing on security and accuracy.

security and accuracy of biometric

Image: Security and accuracy are the most important factors for a biometric modality (representational)

Seeking the most secure and accurate biometric modality

Since we cannot straightaway jump to the conclusion that this or that biometric modality is the best, let it be a self-conclusive discussion. Seeking the “most secure and accurate” would require close examination of all the available options and comparisons of their strengths as well as weaknesses.

There are a number of biometric modalities we can go on comparing, however, we will only take those modalities under consideration, which are popular and commercially available, i.e. you can actually buy them and have them installed. Taking experimental or still under development modalities (e.g. ear shape recognition or body odor recognition) will make no sense as you will only find them in research labs.

Choosing the perfect biometric modality and system out of so many available options can lead to total confusion, which may even end up in an inappropriate selection if you are someone who is actually looking to deploy a biometric recognition method.

Let’s start, shall we?

Before we jump on the comparison bandwagon, let me ask you a question. What aspects would you consider if you have to buy the most secure and accurate lock? Yes, we are talking about the old school physical lock that comes with a couple of keys. You would probably look for security features like how many levers it has; what metal it is made of (brass, steel, etc.). You may lock and unlock it several times to check the accuracy part. You may also look at the features like how many keys are provided along with it as more keys will give you more convenience to have them as backup keys or to share with more numbers of authorized individuals.

Just the way we look at the security, accuracy and convenience features when buying a lock, understanding and examining different biometric modalities is the way to find out the best one.Let’s figure out the most secure and accurate biometric modality by examining them one by one:

Fingerprint recognition

Fingerprint recognition deserves to be the first in our list while seeking the most secure and accurate biometric modality, why? It is not only the oldest, but also the most developed biometric modality that has a very rich history of human identification. We know how fingerprints found on crime scenes serve as an evidence of presence of the subject on the scene. Fingerprint recognition is now very common at office doors, attendance systems, schools, retail stores and even on smartphones. Now with modern biometric systems, fingerprint recognition is one of the most used biometric modality.

But how did fingerprint recognition advance faster than other biometric modalities? Fingerprint recognition always had technological lead as it was already in use with forensics. As biometric technology grew, forensic and law enforcement were among the early adopters. Fingerprint recognition also had more commercial value than any other systems, which also helped it grew.

Accuracy of fingerprint recognition modality

Earlier when most part of fingerprint analysis and matching used to be done manually, accuracy of fingerprint recognition was dependent on human skills. But now all fingerprint recognition applications, including law enforcement and forensics, are completely automated. This level of automation requires these systems to be adequately accurate. Biometric research firms and solution providers have worked very hard to enhance accuracy of fingerprint identification and their efforts have paid off well. Present day fingerprint recognition systems are sufficiently accurate.

Security of fingerprint recognition modality

Fingerprint recognition has become a widely deployed biometric modality in all sorts of applications. This ubiquity requires fingerprint recognition systems to be secure and immune to spoofing. Modern fingerprint recognition systems make use of many anti-spoofing and liveness detection strategies. They can detect capacitance, pulse, temperature of a finger when placed on the scanner. These characteristics cannot be presented by a spoof or replica. With anti-spoofing and liveness detection methods, it would be safe to say that fingerprint recognition modality offer appropriate security if the system employs anti-spoofing and liveness detection techniques.

Our score for fingerprint recognition


Face recognition

Face recognition is another biometric modality going hand in hand with fingerprint recognition in terms of popularity and deployment. Unlike fingerprint recognition, which requires people to touch the sensor, face recognition systems can scan facial features from a distance as they make use of digital imaging. Since we already have powerful cameras, which can take high quality pictures from a considerable distance, face recognition can also be deployed in security and surveillance applications.

Face recognition is also very popular among smartphone users. They can unlock their phone and authenticate identity using the inbuilt camera of their devices. Let’s examine the face recognition on the parameters of accuracy and security.

Accuracy of face recognition modality

In general, present day face recognition systems are sufficiently accurate, except that they still find it hard to distinguish between faces with similar features. One popular example of this is Apple’s 3D facial recognition solution, called Face ID and used in its consumer electronic products like tablets and smartphones. Despite Apple’s claims of it being super secure, many consumers reported that their twins and even relatives were able to unlock their phone with Face ID facial scan.However, face recognition modality has improved a lot over time. The level of accuracy face recognition has achieved in recent years can be understood from the following findings by NIST:“Recognition Vendor Test (FRVT) 2006 showed that it is possible to achieve a false reject rate (FRR) of 0.008 at a false accept rate (FAR) of 0.001 for well controlled images. The FRVT 2006 also included a set of uncontrolled images taken in hallways or outside with variations in lighting, focus, near frontal pose, and expression, among other factors. For these images, the best reported performance was a FRR of 0.12 at an FAR of 0.001; among the better algorithms, the FRR ranged from 0.12 to 0.38 at an FAR of 0.001.”

Security of face recognition modality

Face recognition was once used to be avoided for high security applications and early implementations were highly prone to spoof attacks. Imposters were able to circumvent them with photographs and video clips of an authorized user. However, it has improved in recent years by leveraging 3D facial scan, infrared imaging, etc.

Since face recognition systems can identify people from a distance; they are already being deployed in some interesting applications. We all have seen it in sci-fi movies how smart displays provide necessary information when a user approaches them. This is no more a science fiction now and efforts like this are already underway.

Retail stores are adopting facial recognition to implement security as well as improve user experience. Now there are systems that can track your in-store actions and create a profile out of it. For example purchase history, items you pick up, time you spent on a particular section, etc. So next time you pass by a display equipped with the facial recognition technology, it will show offers specially tailored for you. That’s not all, retail giant Walmart is using facial recognition technology to catch shoplifters.

Security of face recognition modality is enhanced when deployed with liveness detection techniques so that an imposter may not gain access with presentation attacks like pictures or video of an authorized user. 3D map of the facial features and requirement of blinking eyes or smiling for a successful face scan are some of the methods implemented to improve security in face recognition.

Our Score for Face Recognition


Iris recognition

Among all the eye-based biometric recognition approaches, iris recognition is the most prominent one, which has been deployed in a wide variety of applications. Unique muscular folds found in human iris are the basis of iris recognition. These patterns are believed to be unique for an individual and can be mapped with biometric pattern recognition techniques. Automated system for enrollment and verification of identities with iris pattern is called an iris scanners, a device specially designed for the purpose.

Accuracy of iris recognition modality

Iris recognition systems are very accurate and have been deployed in many low to high security applications for personal identification. Due to the high level of accuracy, iris recognition systems have been deployed for identification of travellers in air travel, civil identification in large scale civil identity applications, and even in mobile phones for authenticating transactions.

Security of iris recognition modality

Unlike many other popular biometric modalities like fingerprint and face, which stay exposed and can be collected without a subject’s consent, iris pattern securely resides in the eye behind the cornea; yet, its details can be captured without the need of any expensive setup. Iris recognition systems work by analysing image captured with near-infrared, and map it mathematically to generate a biometric template unique to the subject.

Security threats to these systems are presentation attacks with high quality images with detailed iris pattern, replicas, high quality videos, etc. Security of these systems is enhanced when anti-spoofing and liveness detection techniques like Spectral ICA Analysis to weed out spoofers.

Our score for iris recognition


Voice recognition

Voice recognition is a broad term that includes speaker recognition as well as speech recognition. Speech recognition is about recognition and translation of speech into text while speaker recognition is about seeking the identity of the speaker. Since biometrics is about identification of individuals, phrase “biometric voice recognition” also interchangeably used for speaker recognition.

Accuracy of biometric voice recognition

You may have used phone banking service or have at least called a call center at some point of time in your life. We may know feel it but there is a good chance that your bank or financial service provider is using a voice recognition system to verify your identity when you call them. In such specific applications, these systems are fairly accurate.

If you ask for weather information from your digital assistant like Siri or Alexa on your smart device, most of the time, they will understand your question in first go. If you authenticating an online purchase, they will verify your identity with your voice sample and make a purchase. In recent years, voice recognition has become a hot biometric modality given its increasing use on smart device, and big tech firms working on voice recognition its accuracy is set to improve.

Security of voice recognition modality

Voice recognition is not very evident in physical access control applications, however, it is widely used in specific applications like account security in phone banking, information security (e.g. user voice verification by digital assistant for making an online purchase). Intelligence agencies have been using it for surveillance applications by tapping phone calls of suspects. One of the major security concern with voice recognition systems is that they may not be able to distinguish user voice with his/her recorded voice, so they may not be ideal for applications in which level of required security is high.

Our score for voice recognition


Vein recognition

When it comes to security and accuracy, we just cannot skip biometric vein recognition methods. Palm vein and finger vein recognition are the popular vein recognition methods. Both the methods are fundamentally same and make use of unique vein patters found beneath the skin of palm and fingers in human hand. Vein recognition is also called vascular biometrics. Since it is not possible to capture these details with normal camera and scanning method, a special setup that makes use of near-infrared and CCD (Charge Couple Device) camera is required.

Accuracy of vein recognition modality

Vein recognition is considered to be one of the most accurate biometric modalities. How veins of a person will form pattern beneath the skin is highly random phenomena and they are considered to be unique for each individual. Vein recognition systems are also highly accurate systems to map and match vein patterns.

Security of vein recognition modality

This is where vein recognition modalities excel. Vein recognition is considered to be one of the most secure biometric modalities. Vein pattern stay hidden beneath the skin surface and is not visible from naked eye. They cannot be collected without user consent like fingerprint or face recognition. People do not leave them behind like fingerprints while touching any surface. They are highly immune to spoofing as it is virtually impossible to create a replica of vein patterns. That is why vein recognition systems are often considered when need of security is high.

Our score for vein recognition


Verdict: vein recognition takes the crown

Vein recognition or vascular biometrics takes the crown of being the most secure and accurate modality due to so many advantages it inherently offers. Vein pattern is not visible and collectable like facial features (and even fingerprints) but they are also not as hard to collect as retina pattern. Vein pattern does not change throughout the lifetime of a person. Cost of recognition system is also fair given the so many advantages it offers. Retina recognition is also considered a super secure modality but due to its highly invasive nature, it causes user inconvenience.

So, if you are looking for a super secure and accurate, yet affordable biometric modality, vein recognition is the way to go.