Article 4 min

Deepfake Detection: How to Spot Phony IDs and Prevent Identity Theft


April 24, 2024  

The sophistication and availability of AI-generated images highlight the importance of deepfake detection capabilities during remote identity verification.

Without preventive measures, organizations can open themselves up to increased fraud and compliance failures.

Forward-thinking identity verification providers, though, have long been aware of deepfake and injection attack risks and have developed countermeasures. The same AI innovations that led to deepfakes can be used to thwart them, particularly when organizations combine that technology with layered verification techniques.

An Overview of the Deepfake Arsenal

Organizations across industries around the world are paying close attention to the proliferation of fraud attack vectors. A Bloomberg report underscored the growing concern. 

“Financial crime experts at major banks, including Wells Fargo & Co. and Deutsche Bank AG, say the fraud boom on the horizon is one of the biggest threats facing their industry,” according to the report. 

Those attacks can affect the identity document verification process in a variety of ways.

Fake Identity Documents

Deepfake technology allows malicious actors to create convincing fake identity documents, such as driver’s licenses or passports. Those documents can be used to challenge identity verification checks.


Attackers can use deepfakes to impersonate legitimate people in video or audio recordings, making it appear as if they are presenting their identity documents during verification. 

Injection Attacks

Injection attacks involve inserting malicious data into a legitimate process. Attackers can inject manipulated images, data or biometric information into the verification process to dupe the system.

Biometric Manipulation

Deepfake technology can be used to manipulate biometric data, such as face images or fingerprints. Attackers can present fake biometric data that matches the stolen or forged identity documents, making it difficult for verification systems to detect fraud.

Mitigate Deepfake Risks

As deepfake technology evolves, so do the algorithms and strategies that defend against it.

Identity verification systems can apply a variety of detection methods.

Forensic Analysis

Examine digital footprints to identify inconsistencies or artifacts left behind during the attack.

Biometric Analysis

Compare the presented facial features to known patterns of the person being impersonated. That involves recognizing discrepancies that suggest manipulation.

Pattern Recognition

Use machine learning algorithms to analyze patterns and look for deviations from normal human behavior.

Metadata Examination

Inspect metadata to identify irregularities that may indicate manipulation.

Deep Learning Models

Develop and train AI models to recognize the subtle patterns and inconsistencies associated with deepfake content.

Identity Document and Nondocumentary Verification

Organizations face the constant challenge of adapting to evolving fraud attack vectors, and deepfakes only raise the stakes. Trulioo can help with continuously trained machine learning models that can stay ahead of deepfake technology and injection attacks. 

Trulioo deploys an array of fraud defense capabilities.

Liveness Detection

Trulioo passive liveness detection and document liveness checks help ensure the presented biometric data and document are from a live person and not a static image or deepfake.

Facial biometric checks can establish a more powerful defense against fraud, particularly when the technology has iBeta certification showing it meets globally recognized performance standards for presentation attack detection and biometric recognition performance.

Anti-Tampering Measures

Trulioo anti-tampering features include machine-readable zone and watermark checks on identity documents to spot forgeries.

Image-Capture SDK

The Trulioo image-capture SDK enables apps to require a live photo of a document. Most deepfakes are digital images, so real-time capture ensures a person is presenting a document rather than an AI-generated photo.

Verification Layers

The more verification layers an organization applies during onboarding, the greater the chance to detect deepfakes. Often, a deepfake has no corresponding real-world data, so Trulioo can apply Identity Document Verification and then cross-reference the information through Person Match data verification.

Multilayered identity verification gives organizations the tools to build a strong defense against all fraud, including deepfakes.

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