AMR Future Brief| A Brief Overview of the Top 3 Trends Influencing Biometric Authentication Technology in 2024

As the penetration of the Internet and digital services has increased globally, the need for robust cybersecurity systems has grown immensely. Over the years, different kinds of cybersecurity solutions have been developed to reduce the problem of fraudulent access and duplicity. Among all such recently developed solutions, biometric authentication is one of the most efficient, robust, and reliable cybersecurity technologies, as it involves the use of unique bodily features and characteristics of an individual for identification and granting access.?

Deploying edge computing technologies to improve the quality of biometric authentication?

Over the years, biometric authentication, too, has undergone a huge transformation due to the introduction of advanced technologies like edge computing. Edge computing, in the most basic sense, is a decentralized computing model that brings computation closer to the data source. The main purpose behind decentralization is to reduce the latency and bandwidth use required for data transfer.?

Traditionally, biometric authentication systems run on a centralized server which stores all the biometric records of the individuals who have been registered or identified. When a person provides his/her biometrics, the data is sent to the central server for authentication. If the records are matched with the data on the server, it notifies the device that the user is authorized, and then, access is granted accordingly. Thus, using a centralized computing model for biometric authentication increases the latency and results in delays in identification processes.?

Edge computing, on the other hand, allows for biometric authentication locally on a device, i.e., the individual biometric records are stored on the device itself and when a person provides his/her biometrics, the authentication becomes much faster and easier. The on-device processing offered by edge computing drastically reduces the latency of the system and increases its security and reliability.?

Use of multifactor authentication (MFA) and blockchain to enhance the security of biometric systems?

Conventional biometric systems have a single layer of security, meaning only one set of data is used to ascertain the identity of the individual and grant him/her access. However, single-factor authentication systems can be easily breached, and the data stored in them can be tampered with. To counter these issues, a new security model called multifactor authentication (MFA) has been developed which, as the name suggests, makes use of multiple identification parameters to grant access to a user.?

Thus, biometric systems using multifactor authentication (MFA) techniques, along with relying on biometric data such as fingerprints, facial patterns, and iris images, make use of other factors like phone numbers, one-time passwords, USB keys, etc. Today, MFA is generally used to protect highly confidential and sensitive data such as financial transactions, medical and healthcare records, etc., which demand extra security and privacy.?

Along with this, biometric systems are increasingly using blockchain technology to store data in a decentralized manner. Also, blockchain allows storing of biometric data in an encrypted manner which enhances the privacy of the user. Since blockchain technology is an immutable ledger, the data stored in the system remains tamper-proof and only the owner of the data can make the changes in his/her biometric data.?

Growing shift from physical biometrics toward behavioral biometrics?

Generally, biometric authentication systems check for physical characteristics such as fingerprint scans, facial recognition, iris recognition, etc. However, in the past few years, IT companies have launched solutions that focus on behavioral patterns such as cursor movements, typing rhythms, keystroke analysis, cognitive biometrics, signature analysis, etc. Just like multifactor authentication, behavioral biometrics, too, offers an additional layer of security. Also, cybersecurity systems built using behavioral biometrics offer more convenience, flexibility, and efficiency in detecting unusual patterns.?

Due to these advantages, behavioral biometric authentication systems are employed especially in banks and financial institutions. As most of the banking services are now digitized, financial institutions partner with IT companies to develop mobile applications for providing these services. While developing these applications, IT companies integrate behavioral biometric technologies to track and analyze how the user uses the app and records the services that are most frequently availed by him/her. Using this data, the app provides access to users the next time they try to log into their accounts.?

Recently, in August 2023, BioCatch?, a cybersecurity company, announced the launch of Connect? Portfolio, a fraud and anti-money laundering detection solution. The technology is designed to offer a targeted approach to track, analyze, detect, and monitor fraudulent activities and identify the criminal elements accordingly. For this, the solution makes use of behavioral biometric intelligence, which is powered by AI-based tools and machine learning algorithms, to accurately study the different traits of the user in real-time.?

Summing up?

In conclusion, biometric authentication systems have gained quite a reputation in the past few years as a reliable, efficient, and robust cybersecurity solution. Over the years, as with any other technology, biometric authentication has witnessed massive evolution with the introduction of edge computing and blockchain technology. Furthermore, multifactor authentication and behavioral biometrics have created new opportunities for growth in the biometric authentication industry.?

For more information on the latest developments and upcoming trends in biometric authentication technology,?contact us, today!??

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? **?????????????? ????????????: Akhilesh Prabhugaonkar?

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