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The Different Types of Biometric Spoofing in Modern Security Systems

With the sudden increase during and after the pandemic of remote and digital financial transactions and other systems, the adoption of biometric authentication technologies to protect private spaces, accounts, and systems has also skyrocketed.

But with the increased use of these systems, attempts to hack, trick, and bypass them have also increased significantly. For biometric authentication, this takes the form of biometric spoofing. But what do these spoofing attacks look like? And how can modern authentication systems counter them? Let’s talk about that in today’s blog.

What is Spoofing?


A spoofing attack in the world of cybersecurity is when a person with malicious intent pretends to be someone else with the goal of tricking either a system or a person into providing them access to an account, system, data, funds, or other valuable assets.

Spoofing attacks can happen on a wide variety of different channels and systems, from visual to audio. A biometric spoofing attack for example can take the form of fingerprint spoofing, face spoofing, voice spoofing, and so on.

A biometric spoofing attack can involve varying levels of technical complexity. Some spoofing attacks have a higher level of realism than others. Some more in-depth attacks are tailor-made to target the specific vulnerabilities of a target system. 

Different Forms of Spoofing Attack

As stated, spoofing attacks can come in many different forms, a single form of security system can be victim to multiple kinds of spoofing attacks. Here are the most common ones:

Fingerprint Spoofing

A fingerprint spoofing attack takes the form of fake fingerprint molds created from materials like silicon, rubber, or gelatin so that it is closer to the malleability of a human finger. To make this kind of fingerprint, an already existing digital copy is often used, or sometimes a fingerprint mark is captured from a surface that catches prints easily.

This kind of spoofing can also happen through a print-out of a fingerprint on a specially designed paper or transparent film that can re-create the intricate patterns that are found on a fingerprint. This is done through special high-resolution printers capable of this task, which means that it is often quite expensive.

Newer advancements in 3D printing technology are also being utilized nowadays to create more realistic and accurate three-dimensional replicas of fingerprints of people. Although newer, these have the potential to be the most dangerous forms of spoofing in the field of fingerprint scans.

Face Spoofing

Basic facial spoofing is the easiest to perform out of all the forms of spoofing, but that also means that it is the least effective. This can involve simply presenting a printed-out 2D photograph or digital image of an authorized face in front of the camera or detection system. High-quality videos of authorized individuals are also sometimes used for a more realistic-looking representation of a face.

This is also what constitutes the majority of online spoofing attacks, which are when a person pretends to be someone else online to get you to provide them with your private data, or send them funds.

The more advanced tier of facial deepfakes comes in the form of 3D masks made of the potential victim using materials like silicone or latex, that can achieve a high level of resemblance to the target individual’s face.

The most advanced form of facial spoofing technology and the most dangerous form is the deepfake. These use enhanced artificial intelligence systems and machine learning techniques to learn how a face moves in real-time. This allows the system to implant the target face on a piece of footage with a level of accuracy never previously possible.

Voice Spoofing

This kind of spoofing at the most basic level is the second easiest after basic facial spoofing. The simplest form of voice spoofing is to use a recorded audio of the voice of an authorized user to trick the system into providing you access.

Modern advancements in artificial intelligence, including the invention of large-language models as well as machine learning have created the possibility of creating voice output of a person’s voice, making them say whatever you want them to. This spoofing technology can form highly realistic audio data as the system is recreating the exact cadence, tone, and pitch of the original speaker with complete accuracy.

Modern voice conversion is also sometimes used where a person’s voice can be modified to sound like the authorized user, but the accuracy of this kind of system varies with the processing software used for the purpose, so it can be quite dangerous if the quality of the software and process is high.

Closing Thoughts

With the many different kinds of spoofing attacks that exist, modern countermeasures like liveness detection have been created to counter these systems and to ensure that unauthorized access using synthetic recreations of individuals can be prevented.

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