The Growing Threat of Deepfakes to Identity Verification Processes

Key Takeaways:

What are Deepfakes?

Deepfakes are synthetic media created using artificial intelligence (AI) and machine learning technologies to manipulate or generate visual, audio, or text content that convincingly mimics real people. They can replicate a person’s appearance, voice, or movements so accurately that it becomes difficult for the human eye—or even some digital detection systems—to distinguish between authentic and fabricated content.

Deepfakes are primarily generated using deep learning algorithms, particularly Generative Adversarial Networks (GANs). GANs consist of two neural networks: the generator and the discriminator. The generator creates fake media by learning from a large dataset of real examples, such as photos, videos, or audio recordings. Meanwhile, the discriminator tries to differentiate between real and fake media. Through iterative learning, the generator becomes increasingly adept at producing content that the discriminator can no longer identify as fake. The result is a highly convincing deepfake, which can take the form of videos, audio, images, or even text.

The Malicious Use of Deepfakes

Deepfakes manipulate visual, audio, or text content to portray individuals as having said or done things they never actually did. While some deepfakes are created for entertainment or ethical purposes, they are increasingly linked to malicious activities. As the quality and accessibility of deepfake technology rapidly advance, it has become easier for individuals with minimal technical expertise to produce convincing forgeries. This democratization of deepfake creation tools has led to a rise in their use for malicious purposes.

The malicious use of deepfakes extends beyond spoofed images, videos, or voice notes of politicians and influencers. Deepfakes have played a key role in misinformation campaigns and fake news stories, particularly on social media. The proliferation of deepfakes has eroded trust in digital content, making it more difficult for users to distinguish between real and fabricated information.

The financial impact of deepfakes has been significant. For example, an employee was deceived by a deepfake audio mimicking his CEO’s voice and transferred $243,000 to a fraudulent account. Similarly, a finance worker in Hong Kong was tricked into paying $25 million after attending a deepfake video conference.

The Growing Threat of Deepfakes in Digital Identity Verification

Deepfakes pose a significant threat to identity verification processes by creating highly convincing, AI-generated forgeries that can bypass biometric security measures. This makes it challenging for verification systems to distinguish between genuine and fake identities, allowing criminals to evade critical protocols like facial recognition and Know Your Customer (KYC) checks.

According to Sensity’s annual report, there are 2,298 tools available globally for face swaps, lip syncs, and AI avatars, along with 10,206 tools for AI image generation. Additionally, 47 tools specifically designed to bypass KYC processes have been identified. In underground markets, ready-made photos and videos for bypassing KYC checks are sold for as little as $5 to $20. One such website, OnlyFake, claims to use “neural networks” to generate realistic-looking photos of fake IDs for just $15.

For financial institutions and customers, the risks of deepfakes are significant, leading to financial losses, identity theft, and reputational damage. Criminals exploit deepfakes to manipulate verification systems, undermining personal security and the integrity of businesses worldwide.

As digital identity verification gains importance, it becomes crucial to accurately confirm individuals’ identities. However, with the growing sophistication and accessibility of deepfake technology, institutions must implement advanced detection systems to mitigate these evolving threats. 

The KYC Process: How It Works and Why It’s Vulnerable

Know Your Customer (KYC) is a crucial process used by businesses, particularly financial institutions, to verify the identity of their customers. Its primary goal is to prevent financial crimes such as money laundering, fraud, and identity theft by ensuring that customers are who they claim to be. KYC requirements became more stringent after 9/11 and have evolved over time.

The KYC process involves collecting and validating customer information, such as names, addresses, and government-issued IDs (e.g., passports, driver’s licenses). It also includes risk assessment, ongoing monitoring, and enhanced due diligence. These measures help businesses comply with local and international regulations aimed at preventing illicit activities.

Traditional KYC methods involve collecting physical documents and, in some cases, conducting face-to-face interviews. This can be time-consuming, labor-intensive, and inconvenient for customers, especially in remote areas. To address these challenges, electronic KYC (eKYC) was introduced. eKYC allows customers to verify their identity online by submitting digital copies of documents, which are verified using technologies like optical character recognition (OCR) and artificial intelligence (AI). Biometric verification, such as facial recognition or fingerprint scanning, adds an extra layer of security. This digital approach makes KYC faster, more efficient, and accessible, enabling remote onboarding and improving convenience in regions with limited physical infrastructure.

How eKYC Verification Works

The eKYC verification process typically involves a few key steps:

1. ID Verification: This step involves confirming a customer’s identity by comparing the information on their government-issued ID (such as a passport or driver’s license) with the data provided during registration. The ID is scanned or photographed, and optical character recognition (OCR) technology extracts the necessary details for verification. Advanced systems cross-check this information against authoritative databases to confirm its authenticity.
2. Face Matching: After verifying the ID, the system compares the customer’s face with the photo on the ID. To facilitate this, companies usually ask customers to take a selfie, sometimes holding the submitted ID. Facial recognition technology then ensures the person presenting the ID matches the photo on it.
3. Liveness Detection: To prevent spoofing attacks, liveness detection is used to verify that the individual is real and not a static image, video, or digital representation. This process may involve actions like blinking, smiling, or turning the head, which the system captures to ensure a live person is completing the verification.

Vulnerabilities in eKYC: How Deepfakes Bypass Security

Deepfakes pose a significant threat to the reliability of eKYC systems by creating convincing but fraudulent biometric data. These forgeries can trick biometric verification systems, which are essential to eKYC. As deepfakes become more advanced, distinguishing between real and manipulated data becomes increasingly difficult, allowing criminals to impersonate individuals and commit KYC fraud. This vulnerability undermines the security of eKYC processes, making it easier for fraudsters to bypass KYC checks and gain unauthorized access to accounts and services.

Biometric verification methods, including fingerprint scanning, facial recognition, and voice recognition, has long been considered one of the most secure methods of identity verification. However, deepfakes exploit several vulnerabilities. Fraudsters can create highly convincing forgeries of government-issued IDs, alter faces in selfies to match stolen or fake IDs, and bypass facial recognition systems. Liveness detection, which verifies physical presence, is also at risk. Deepfakes can mimic movements like blinking or smiling and even use pre-recorded videos to trick systems. According to a report by Onfido, biometric fraud attempts using deepfakes increased 31 times in 2023 compared to previous years, signaling a growing sophistication among fraudsters in using advanced tools to circumvent security measures.

Common Types of Deepfakes Used in Identity Fraud

Various types of deepfakes are commonly used in identity fraud:

• Face Swaps: Face swaps replace the face in a video or image with someone else’s, creating a realistic but fake representation. Fraudsters use this technique to match a stolen ID’s photo with their own face, bypassing facial recognition systems. In some cases, they blend features from multiple faces to create a synthetic identity that appears real. This method can be combined with voice cloning to manipulate videos, making it seem as if a person is saying something they never did, a technique known as lip-syncing.
• Fully Generated Images: AI can create entirely new faces that don’t belong to any real person. Criminals can use these fully generated images to create synthetic identities that pass as genuine in KYC checks.
• Voice Cloning: Voice cloning deepfakes use AI to manipulate audio content. They can create or replicate a person’s voice accurately.
• Synthetic Identities: Fraudsters combine real and fake information to create entirely new identities, which are difficult to detect using traditional KYC methods. They use these deepfake identities to open bank accounts, apply for loans, or engage in other types of fraud.

Verifiable Credentials as a Solution to Identity Verification Processes

Verifiable credentials (VCs) are cryptographically secure digital attestations that verify specific claims, such as identity, qualifications, or attributes. Issued by trusted authorities, VCs can be independently verified without relying on centralized databases, making them resistant to tampering and fraud. In KYC processes, VCs provide robust protection against deepfakes by offering verifiable proof of identity that cannot be easily forged or manipulated.

The structure of a VC includes:

• Issuer: The entity that creates and signs the credential.
• Holder: The individual or entity that controls and shares the credential.
• Verifier: The party that checks the credential’s validity using cryptographic methods.

How Verifiable Credentials Combat Deepfakes in Identity Verification Processes

Here’s how VCs address deepfake challenges:

1. Cryptographic Security

VCs rely on cryptographic technology that embeds digital signatures into credentials. These signatures validate the authenticity of the credentials, ensuring that any alteration by deepfakes immediately invalidates the signature. Verifiers can cross-check this signature against the issuer’s public key, confirming the credential’s legitimacy. This level of cryptographic security makes it nearly impossible for deepfakes to forge or manipulate documents without being detected.

2. Immutable Records

Blockchain technology or distributed ledger systems play a crucial role in recording verifiable credentials. These systems create immutable records, meaning any attempt to tamper with or alter a credential leaves a trace. This transparency ensures that blockchain records quickly flag and invalidate deepfake-manipulated credentials, as any modification is permanently recorded.

3. Selective Disclosure

With verifiable credentials, only the essential information is shared, preventing overexposure of sensitive data. For instance, a user can prove they are of legal age without revealing their full date of birth. This ability to disclose minimal information reduces the risk of deepfakes exploiting personal data, offering an additional layer of privacy protection.

4. Decentralized Control

Verifiable credentials are linked to decentralized identity systems, removing reliance on vulnerable centralized databases. Individuals control their credentials through secure digital wallets, and verifiers independently confirm their authenticity through decentralized networks, reducing the risk of deepfake identity spoofing.

5. Preventing Identity Spoofing

Cryptographic keys tie each VC to a specific individual, making identity spoofing virtually impossible. Even if a deepfake video or image is presented, cryptographic checks ensure the credential is authentic, preventing fraudsters from using deepfakes to impersonate real identities.

6. Enhanced Privacy and Security

The use of advanced cryptographic techniques also limits the amount of data shared during identity verification. By minimizing the exposure of personal information, verifiable credentials reduce the attack surface for fraudsters. This makes it difficult for deepfakes to gather enough data to carry out successful fraud.

7. Efficiency and Interoperability

VCs streamline the identity verification process by reducing manual checks and leveraging automated cryptographic validation. Their interoperability across platforms and regions ensures a consistent global solution, making it harder for deepfakes to exploit gaps in international KYC and identity verification systems.

The Future of Identity Verification and Verifiable Credentials 

As deepfake technology becomes more advanced, the role of verifiable credentials (VCs) in KYC and identity management will become even more critical. VCs offer a proactive and secure solution to the growing threats posed by deepfakes, ensuring that identity verification processes remain reliable and resilient.

1. Widespread Adoption: With the rise of deepfake attacks, financial institutions, governments, and organizations are expected to accelerate the adoption of verifiable credentials. VCs are highly scalable, enabling their use across various industries and regions. Their cryptographic foundation ensures that as deepfake technology evolves, VCs can continue to offer a high level of security, adapting to new challenges and minimizing fraud risks.
2. Integration with Digital Identity Systems: Verifiable credentials will become a core component of digital identity ecosystems, especially as decentralized identity models gain momentum. This integration will provide individuals with a seamless and secure way to manage and verify their identities across multiple platforms. As a result, significantly reducing the risk of deepfake-driven fraud.
3. Enhanced Security Protocols: To counter the evolving threat landscape, security protocols for verifiable credentials will continue to advance. The use of cutting-edge cryptography, blockchain, and AI-powered detection systems will play a critical role in protecting KYC processes from deepfake attacks, ensuring long-term security and trust.

Conclusion

Identity.com

Identity.com, as a future-oriented organization, is helping many businesses by giving their customers a hassle-free identity verification process. Our organization envisions a user-centric internet where individuals maintain control over their data. This commitment drives Identity.com to actively contribute to this future through innovative identity management systems and protocols.

As members of the World Wide Web Consortium (W3C), we uphold the standards for the World Wide Web and work towards a more secure and user-friendly online experience. Identity.com is an open-source ecosystem providing access to on-chain and secure identity verification. Our solutions improve the user experience and reduce onboarding friction through reusable and interoperable Gateway Passes. Please get in touch for more information about how we can help you with identity verification and general KYC processes.