Evaluating Algorithm Effectiveness for Fingerprint Technology
Today’s fingerprint scanners’ performance and security are heavily reliant on their matching accuracy and ability to keep errors under control. Fingerprint recognition devices will become more of a problem than a solution if they fail to maintain optimal matching accuracy and error control mechanisms.
Fingerprint scanners are becoming increasingly popular and are being used in a variety of applications.
One of the reasons for the increasing popularity of fingerprint recognition devices is their ability to strike a delicate balance between convenience and security. However, there are still a number of issues, errors, and limitations that this technology must address.
What are the various types of fingerprint matching errors? What are the limitations of fingerprint biometrics and how is the fingerprint error rate calculated?
How trustworthy is fingerprinting as a method of identification?
Fingerprint technology has extremely high accuracy, but this accuracy is dependent on a number of factors. The likelihood of false positives is nearly zero, and it could be completely eliminated with the help of live scanning. However, if proper scanning is not performed, there is a high risk of false negatives.
The friction ridges on the fingers form distinct patterns that are unique to a person, and minutiae points formed at ridge ending and ridge bifurcation are extracted from these patterns to be used later for verification or identification.
The first major factor influencing fingerprint scanner accuracy is human error. When a sensor reads a fingerprint, it generates multiple digital templates using minutiae points, which are then saved in a database for future matching.
False negatives occur when the subsequent fingerprints captured are insufficient to create templates for database matching. Enrolling more than one finger usually solves the majority of these issues.
Device capabilities are also important in the recognition process. Because the minutiae points are quite subtle and skin conditions may interfere with proper template formation, it is critical that the device is capable of capturing the best possible images even when the external conditions are less than ideal. A primary deciding factor is DPI (dots per inch), which refers to the amount of information stored in a digital image within an inch of space.
Fingerprint matching: Precision is essential
A wide range of applications now rely on automated fingerprint recognition to function. This
reliance has grown to the point where applications will become inoperable if fingerprint recognition technology is removed. One of the key factors driving the popularity of fingerprint biometrics is the technology’s unrivalled balance of convenience and security.
The fingerprint scanners must strike a delicate balance between security and convenience. They would become inconvenient if they were designed to be highly secure. However, the high level of convenience would jeopardise security. As a result, maintaining this balance is critical to ensuring user convenience as well as an optimal level of authentication security.
This security-convenience trade-off is also why, even when you present your registered fingerprint, fingerprint scanners will sometimes refuse to let you through.
If they find your scan to be lacking in details or clarity, they may request a rescan to ensure that the person seeking access is indeed the authorised person.
Accuracy is critical in ensuring that the security-convenience balance is maintained. Accuracy is determined by a variety of factors, including the scanner’s components and technology, environmental factors, and the quality and usability of user fingerprints.
Limitations of fingerprint biometrics
Fingerprint biometrics has advanced to the point where it can be used securely for personal identification and authentication in applications ranging from low to high security. This technology can be customised for high security as well as convenience-oriented use cases. It can also be used in conjunction with other authentication factors to provide even greater security by enabling two/multi-factor authentication.
However, there are many limitations and challenges to address in fingerprint biometrics.
The major limitations of fingerprint biometrics are as follows:
- Presentation spoofing and attacks
Despite unprecedented growth and advancements in biometric fingerprint recognition technology, spoofing remains the technology’s most difficult challenge. Biometric spoofing is a method of circumvention in which a forged replica is presented to a biometric system in order to defeat its security. To be able to bypass the systems, this replica must have the exact biometric pattern.
- The immutability of biometric identifiers
Biometric identifiers are unchangeable in nature, which means they cannot be changed like a password or PIN or reissued like IDs if they are compromised. If a cybercriminal is able to capture your biometric patterns, he or she can create spoofs to circumvent a biometric system on which you are registered.
- Technology-related constraints
Biometric systems, like all other technologies, have technological limitations. Today’s fingerprint recognition systems can work in harsh environmental conditions as well as difficult scenarios, but they can only go so far. Excessive humidity, extreme temperature, intense ambient lighting, and other harsh environmental conditions, for example, may cause them to break. Although technical failures are uncommon, they do occur. Because fingerprint recognition systems are electronic devices that rely on electricity to function, power outages/failures render them inoperable.
- Incorrect rejections / acceptances
Modern fingerprint biometric systems have faster response times than ever before, and in 1:1 matching, most systems will only take a fraction of a second to authenticate an identity. However, the biggest issue with these systems is their dependability when used in critical situations where errors like false rejection cannot be tolerated.
In some cases, errors such as false rejections or false acceptances can be fatal, even disastrous. A law enforcement officer, for example, may not be able to afford a false rejection from a smart gun that uses fingerprints to unlock the gun safety lock. When an officer needs to use his or her weapon quickly, the delay caused by false rejection can be fatal.
How companies like NIST evaluate algorithm production of companies like Neurotechnology?
With its Proprietary Fingerprint Template (PFT) evaluation, the highly accredited National Institute of Standards and Technology (NIST) has provided the largest and most recognised ongoing assessment of fingerprint verification available today.
Because fingerprint templates are not always standardised across vendors, each algorithm developer employs cutting-edge technology to demonstrate the full potential of their individual algorithms. The top position of Neurotechnology in PFT III demonstrates the fully enhanced capabilities of the company’s most recent R&D advancements.
Conclusion
The adoption of fingerprint scanners has been astounding over the last few decades. This technology, which was once stigmatised as a method of criminal identification, is now widely accepted. The perfect balance of security and convenience that fingerprint biometrics provides is one of the major factors driving its growth.
Whilst NIST carries out evaluations of fingerprint algorithms to determine the accuracy, they also cover other areas of biometrics such as facial recognition. Biometric technology companies often participate in Facial Recognition Vendor Tests (FRVT) organized by NIST and present their results to the public as shown in this example. There are numerous different types of algorithm assessments when it comes to facial recognition, including ones with and without face masks on. Here you can find an example recipient of an frvt 1:n assessment.
This delicate balance of convenience and security is heavily reliant on the accuracy of fingerprint matching. Several studies have demonstrated that modern fingerprint recognition systems are extremely accurate. However, errors like false acceptances and rejections are still possible with modern fingerprint recognition devices.
