Is This Face Real or a Deepfake? In the Deepfake Era

Is This Face Real or a Deepfake?

"Is this a real person? Or an AI-generated fake?"

It’s no longer something we can judge with our eyes alone.
But what if someone uses that face to apply for a loan, create an account, or transfer money?

Deepfake technology is now embedded in our everyday lives. Videos and images that steal someone’s face or voice are rapidly spreading across the internet.

To combat this growing threat, Denmark became the first country to propose a bill granting copyright rights to an individual’s face, voice, and body. The bill is expected to take effect in 2025, with enforcement linked to the EU’s Digital Services Act (DSA).
Platforms will be required to swiftly respond to individual requests for removal of unauthorized deepfake content or face heavy fines.

What Is a Deepfake?

‘Deepfake’ is a combination of "deep learning" and "fake."
Though the technology has constructive uses in entertainment and education, its misuse for identity fraud and financial crimes is a growing concern.

According to a 2023 iProov report, deepfake-based face alteration attacks surged by over 700% compared to the previous year.

Real-World Risk: Deepfake Fraud

Why is protecting your identity so important?

The image shown above is a deepfake.
It’s nearly impossible for the human eye and often even traditional detection systems to spot the difference.

As deepfake technology evolves, attempts to bypass identity authentication are becoming more sophisticated.
Here’s what ARGOS has uncovered through real-world fraud analysis

Isn't deepfake technology getting more sophisticated?
The synthetic image, which was awkward at first, is now so natural that it is difficult to distinguish at a glance. Some of these faces that look like a real person, including SNS profile pictures, video calls, and even ID photos, are actually 'fake' made by AI entities that do not exist.

The problem is that these sophisticated fakes are not just a joke.
At this moment, somebody uses a deepfake face to apply for financial services, build an account, and send money abroad.
The face created by AI not a real person passes through the authentication system.

How can we distinguish between real and fake?
And how is the technology and law responding to deepfakes?
I would like to introduce ARGOS's unique deepfake discernment technology.

ARGOS' Deepfake Separation Technology

ARGOS analyzes the “frequency pattern” in the image and precisely distinguishes the deepfake.
This is not just a comparison of pixels, but a way of looking at the invisible digital characteristics of the image as if separating the highs and bass from a piece of music.

<Technology Operation Principle>

• Convert the image file to the frequency domain

• Intensively analyze frequency bands that frequently appear in deepfakes

• Apply sigmoid function to pattern analysis

• Determine authenticity based on a comprehensive result

• Precisely correct based on actual photo data

This technology is similar to scanning the "DNA" of the image.
Apparently, the deepfake image is also clearly revealed in the frequency domain.

ARGOS has more than 160,000 actual deepfake image data to increase this analysis accuracy.
Based on this vast learning data, we are continuously learning deepfake patterns and quickly adapting to new attacks.

Beyond simply distinguishing 'deepfake or not', it has a competitive level of technology in both accuracy and response speed.

If so, where is the first industry that should prepare now to prevent deepfake fraud?
Today, we will pay attention to the financial sector.

The Impact on Financial Institutions and Response Strategies

Financial institutions start dealing with customers based on identification.
Therefore, when a stealing fraud with deepfake occurs, the damage is direct and deadly.
In order to effectively respond to these threats, financial institutions need to prepare some key strategies.

First of all, it is important to upgrade the liveness detection technology.
This is a technique that determines whether or not a real person is present by analyzing biometric information such as the user's blinking, fine facial expressions, and skin textures.

In addition, AI-based document forgery detection technology is also required.
Since deepfake attacks are often done with false IDs or synthesized images, a sophisticated analysis system is required to automatically detect detailed elements such as background consistency, letter distortion, or border abnormalities.

At the same time, since deepfake technology is constantly evolving, the detection system must also have a deep learning-based structure that continues to learn and adapt.
To respond quickly to the latest types of attacks, real-time data-based repetitive learning is key.

Finally, it is necessary to establish a system that can identify and block risks in real time through data linkage with fraud histories or sanctions.
Connection with global fraud monitoring networks and integration with internal fraud detection databases are highly effective methods for proactively blocking risks.

When these technical and strategic preparations are in place, financial institutions can provide trust-based services that are not shaken even by sophisticated deepfake-based impersonation attempts.

ARGOS's Reliable Online Authentication Service!

In particular, in recent years, cases have increased where accounts using deepfake faces are used to open multiple accounts through overseas remittance or fintech platforms and then used for money laundering.
Both the faces and IDs used can be fake, generated by artificial intelligence, and it is often difficult to filter them out with existing authentication systems.

To cope with these threats, ARGOS combines deepfake detection technology with AI-based behavioral analysis to block account creation based on false identities.
It does not simply end with a one-time authentication but also monitors the post-authentication process through continuous monitoring and risk detection.

These ARGOS technologies are currently expanding rapidly across various sectors:

• Global digital financial companies: As they serve multinational customers, precise identity verification that can respond to regulations and various threat scenarios is essential.

• Overseas remittance and payment platforms: Since transactions are often small and the remittance routes complex, detection and tracking of false accounts are especially important.

• Web3 and blockchain-based account creation services: In anonymous environments, it is common for a single person to create dozens of wallet addresses. ARGOS can proactively block this with identity-based authentication.

In other words, ARGOS provides trust from customers beyond authentication.
To respond to the new threats brought by deepfakes, financial institutions and fintech services must now consider real-time detection and adaptive security systems that go beyond simple KYC.
ARGOS already offers the answer through technology. Check it out now!