biometrics in artificial intelligence
  • Use of Artificial Intelligence In Biometric Corroboration

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Biometric verification technology is an essential tool for preventing criminal activities. Cybercriminals use sophisticated ways to deceive the system. AI-based biometric authentication solution is an effective solution for eliminating evolving threats of Identity thefts and spoofing attacks. The rapidly increasing threats of digital frauds and identity scams drive the need for incorporating robust ID verification solutions and biometric authentication is the better approach. Let’s have a look at what biometric technology is and the common ways by which fraudsters deceive the system and how it eliminates them.

AI is continuously enhancing the security of sensitive data. It is also trying to secure online transactions as this is really an important aspect for the finance industry. However, cybercriminals are always ready to develop a new technique for data breach. Identity theft has become common these days due to fraudsters. A customer goes for a more secure organization where they can easily access their information anytime and anywhere. Banking sectors are greatly affected due to cyber attacks. But Artificial Intelligence is not coming slow to beat these kinds of frauds and attacks.

What is Biometric Verification?

Biometric verification is mainly used for identity verification. By scanning and matching the unique biological traits and physical features of the person it becomes easier to accurately verify his identity. The walking mode or gait, retina, face, fingerprints, and palms are the unique biometric features commonly utilized for the purpose of ID verification.

Methods Used For Evading Biometric Authentication

Generally, fraudsters use 3D masks to fool the biometric authentication measures. These days, scammers use sophisticated technology to deceive the verification checks. Modifying the content of audio and video files according to the requirements has become a recent trend. Also called deep fakes, cybercriminals use deep learning methods for deceiving people to believe their false positives.

Spoof Attacks

Other than making use of 3D face masks and glasses, there are various other means by which fraudsters carry out spoof attacks. In the digital space, it is not quite difficult to collect pictures of someone and use them for malicious efforts. With the support of advanced technology, they can temper photos and use them during the biometric identification process.

3D Facial Masks

Impersonators use sophisticated technology for generating 2D face masks. If we talk about the recent spoof attacks, they used facial masks of real/genuine people for verifying the picture on the ID document during facial authentication. The biometric security system scans the movement of eyes, face, and smile for detecting facial spoof attacks.

Deep Fakes

Aside from 3D and 2D facial masks, deep fakes are an evolving threat for financial organizations. Impersonators can modify video and audio files according to their requirements. For example, they can change the background of the video and statements so they can appear authentic wherever any information is requested.

Why do scammers tend to use deep fakes?. Because they fully understand that enterprises have employed robust verification checks to secure their information. They need a more sophisticated approach to deceive the system and deep fakes are common ways used by cyber attackers these days. In 2019, cyberattackers copied the voice of the CEO of a renowned energy firm and requested 220,000 euros from the employees. Likewise, the video of the former president of America Obama was also modified in which he used specific names for Donald Trump.


In this technique, hackers try to exploit the biometric security system without implementing any impersonation methods. They exploit the bugs or loopholes in the biometric authentication mechanism and change the data present in the system. For example, scammers can feed a pre-recorded video stream in biometric software. But, robust biometric authentication measures restrict fraudsters from accessing the system. With the assistance of liveness detection checks, hacking attempts can be eliminated at an earlier stage.

How Biometric Authentication Protects Against Spoof Attacks and Hacking Attempts?

User verification measures ensure the live presence of the user. The live selfie uploaded by the user is matched against the picture on his government-issued identity documents. Furthermore, 3D depth perception, AI mapping, skin texture analysis, and different other features assist in detecting spoof attacks in real-time. The user is requested to blink, smile, nod, and talk with the verification expert to identify spoof attacks.

With the application of artificial intelligence, it has become easier for impersonators to devise better spoofing techniques. But, biometric recognition measures have become more robust too. A minor change in the skin color in the image will not allow criminals to bypass the verification checks. Accurately trained Artificial intelligent models and skin texture analysis can identify and mitigate facial spoofing attacks. Additionally, the liveness detection feature is implemented to ensure greater accuracy of the biometric authentication measures.

Wrapping it up

Biometric verification is the ultimate solution for protection against identity thefts, facial spoofing attacks, deep fakes, and 3D face masks. 3D depth perception, AI mapping, skin texture analysis, and liveness detection features enhance the accuracy of biometric authentication systems. Hacking and spoofing are the major techniques by which imposters deceive the biometric authentication checks. Cybercriminals use sophisticated technology in these techniques to perform malevolent activities. But, biometric technology integrated with AI and deep learning can counter spoof attacks.

Kiera Peterson

By Kiera Peterson
who is residing in Australia.

Member since February, 2020
View all the articles of Kiera Peterson.

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