The Future of Authentication: Multi-Modal Biometrics in a Digital World

Unimodal and Multimodal Biometric Sensing Systems:

Individuals are verified and identified using biometric technologies based on physiological or behavioral traits. These characteristics can be divided into multimodal and unimodal biometric systems, with the latter exhibiting various flaws that impair system accuracy, such as noisy data, inter-class similarity, intra-class variation, falsification or spoofing, and non-universality. However, multimodal biometric sensing systems detect and process two or more behavioral or physiological factors to significantly improve identification and authentication success.

Unlike unimodal, multimodal biometrics in a digital world employs multiple tracking technologies that are processed concurrently, boosting the security and confidence of the connection and authentication. These systems can be used on a range of devices and can incorporate, among other things, facial recognition, speech and handwriting recognition, retina scanning, fingerprint identification, etc. One prominent example is the issue of worn fingerprints, which can lead to mistakes. In a multi-factor biometric system, such an error or failure may not have the same impact on the individual as in other biometric systems.

IAMX, a Swiss private business, has launched a multimodal biometrics system that it says can verify digital identities in seconds. Fingerprint readers, liveness checks, face recognition, and ID document readers are examples of biometric sensors. Registration and identity verification are also simplified, as are bookings, access to digital banking, SIM cards and mobile services, medical aid, insurance, and hotel reservations.

Also Read: Digital Identity Management: Enhancing Security Through Blockchain-Based IDV System

Drawback of Biometrics

Various biometric detection technologies were The most effective ways to identify and track persons for private, public, and security purposes. However, numerous forms of biometric detection systems continue to face hurdles. One noteworthy example is that certain unique qualities of persons, such as fingerprints, tend to age, whereas voice biometric devices might present issues in cases of voice loss, making identification difficult.

Some of the challenges faced are

• People with arthritis cannot trust their hands during the examination, so the biometric hand geometry method does not function for them.
• Current face recognition systems encounter numerous obstacles as a result of the variations in the face. Changes in lighting, changes in facial expressions, and, most crucially occlusion
• Even if a person has an eye problem, the iris biometric system can underperform
• The finger or hand biometric identification system needs each user to sign in at all times; otherwise, it uses a comprehensive mechanism for registration and verification.
• A fraudster can utilize voice recognition to record the real voice and exploit it for unauthorized identification.
• Weather conditions, viewing angle, alcohol consumption, and weight can all have an impact on the gait recognition process.
• When the nerve pattern begins to shrink owing to aging and other conditions such as tumors, diabetes, and so on, it makes palm vein recognition difficult.

As a result, these limitations impede the performance of unimodal and multimodal biometric sensing systems while also providing the opportunity for future study.

Multi-Modal Biometrics in a Digital World

The future of biometric identification is multimodal biometrics, which combines numerous biometric identifiers for increased accuracy and dependability. This method integrates several biometric techniques to produce a complete and robust identification system. They add user convenience by reducing reliance on a single feature and eliminating issues like non-enrollment

Is bias a big problem in digital authentication technology, particularly in multimodal biometrics?

Bias is one of the issues that multimodal biometrics confront. This can result in high error rates, delayed reaction times, or an increase in false positives, which can be misinterpreted as fraud.  Bias will become less of an issue when biometrics become more widely used, capture more diversity, and are added to public databases.

The future of biometrics will require model creators to reconsider how they train their algorithms to eliminate biases. Organizations creating biometric identification systems must ensure that algorithms are trained in a variety of conditions and that training datasets are most suited to real-world scenarios. Identity verification systems should give thorough instructions on how to capture the biometric data required to establish their identity to deliver the greatest experience for users.

• Using multimodal biometrics in a digital world improves identification accuracy and security while decreasing false positives and rejection rates.
• Multimodal biometric sensing systems also resist spoofing attacks due to their complexity.
• Perhaps most crucially, multimodal biometrics demonstrates how to build the future of identity verification using decentralized identification like self-sovereign identity and continuous verification
• The future of biometrics is the integration of cloud technologies with biometric systems, particularly as part of multi-factor authentication methods. These cloud solutions improve the company and organizational flexibility, scalability, and security.

How can multimodal biometrics in a digital world contribute to the banking sector?

• By allowing remote access, multimodal biometric authentication can help to speed up onboarding.
• With a few mouse clicks, customers can open bank accounts, e-wallets, consumer applications, loan applications, and insurance policies making KYC easier. Biometrics and digital money exchange are assisting the globe in meeting its investment objectives by ensuring AML compliance.

Also Read: What is Digital Onboarding and How It Works?

In organizations where employees often enter passwords many times per day, how might introducing new and advanced multimodal biometric authentication technologies increase both security and employee productivity?

• IT managers believe that employees enter passwords 12 times per day on average, with 25% entering passwords 20 or more times per day. They assure that their staff lose productivity as well.
• To reduce human labor,  multimodal biometrics in a digital world can be integrated into workplace attendance and sign-in systems. Access control systems with facial recognition and fingerprint readers, on the other hand, prevent identity fraud. Organizations can combine fingerprints, facial recognition, and even voice recognition.

As organizations across industries continue to use biometric identity verification like multimodal and unimodal biometric systems, the era of passwordless authentication is underway. Biometric verification technology has advanced dramatically in recent years, to the point where it is now used in many common tasks, such as unlocking our mobile devices. Even though facial recognition technology may achieve 99% accuracy, fraudsters have devised workarounds such as face morphing, deepfakes, digital image alteration, and the use of synthetic masks.

Why is it expected to become the norm in identity verification and authentication?

The combination of biometrics and security systems enables a more convenient, user-friendly, and efficient approach to establishing identity and verifying identity. Biometric authentication is changing the way we interact with the world, whether it’s unlocking a phone with a fingerprint reader accessing advanced security services with facial recognition technology, or using both in multimodal biometrics. The reliance on biometric authentication will only grow in the future. It’s no longer simply about security; it’s about providing a seamless personalized customer experience. And, as market statistics show, biometric authentication is becoming more prevalent than before.

Also Read: Going beyond Passwords: Implementing eIDV for Safer Banking

Enhanced Security

These concerns will continue to be top considerations for businesses as the new year begins, opening the road for increasing adoption of multi-factor biometrics in a digital world. Adding a biometric authentication layer to the authentication process gives another layer of separation between organizations and bad actors. Combining facial recognition with other biometrics, such as voice or iris recognition, increases security for businesses wishing to authenticate consumers, patients, employees, and other users. Techniques like mouth movement and speech and detecting blood flow in the face make identification far more difficult to fake.

EU has also voted to support the law on the digitalization of the visa which will require multi-modal biometric authentication i.e. both face and fingerprint recognition. The application system for voluntary will be available in 2025 while mandatory use of biometrics will be implemented in 2031-32.

What is the significance of using multimodal biometric authentication in deployment in the future?

In terms of deployment, it is anticipated that multimodal biometric identification will become more popular. The move from one-time authentication to continuous authentication is gradual, with advanced behavior patterns used for better security. The market is launching new biometric authentication methods. The cutting-edge technology will be able to identify the user by employing more complicated and hence more difficult biometric signals such as hand geometry, heartbeat patterns, and even smell.

Despite its benefits, biometric technology poses difficulties. Biometric technologies are being improved by researchers and developers to solve potential weaknesses and increase overall security in multimodal and unimodal biometric systems. In multi-factor authentication (MFA) systems, combining biometrics with other authentication factors (such as passwords or tokens) improves security and helps reduce risks.

Concerns concerning privacy, data security, and the possibility of compromised biometric data are areas of continuous research and development in cybersecurity. To address these concerns, robust anti-spoofing technologies and digital authentication technologies, as well as encryption and secure storage of biometric data, are constantly being developed to maintain the integrity and secrecy of the biometric authentication process.