Protecting from the Rising Threats in Video Communication

Cyber fraud is skyrocketing, with deepfake-related crimes increasing by over 300% in the past year alone.

A recent study found that 37% of businesses have already encountered deepfake scams, and experts predict that AI-generated fraud could cost companies over $5 billion annually by 2027.

As AI-driven deception becomes more sophisticated, the need for robust authentication methods has never been greater.

The rapid advancement of Generative AI (GenAI) has introduced new threats to video-based communication. AI-powered tools can now seamlessly swap faces, mimic voices, and even create entirely synthetic identities in real time.

What was once a concern limited to deepfake videos has now evolved into a full-blown security crisis where fraudsters can infiltrate meetings, conduct interviews, and manipulate business processes—all without revealing their true identities.

Real-World Fraud Cases: Lessons Learned

One stark example is the North Korean IT worker fraud scheme, where operatives used deepfake technology to secure remote jobs in Western tech companies. These individuals disguised their identities using manipulated video and voice feeds, bypassing traditional biometric and document verification checks. (Read more)

Another growing concern is the use of deepfakes in student interviews, where AI-generated personas are being used to deceive educational institutions and secure admissions under false pretenses. (Read more)

Why a Single Biometric Check is No Longer Enough

Relying on a single biometric factor—such as face recognition—poses significant risks in this new landscape. For instance:

• Camera-Off Scenarios: If a fraudster disables their video feed during a meeting, face recognition becomes useless, allowing voice-based deception to take over.
• AI Voice Cloning: Even if voice verification is used, advanced AI tools can replicate a person's voice with near-perfect accuracy.
• Synthetic Identity Attacks: Attackers can combine multiple AI techniques to create a seemingly legitimate presence that evades both human and automated verification methods.

Demonstrating the Risk: Real-Time Face Swaps in Meetings

To illustrate just how easy it is for fraudsters to manipulate video calls, we’ve created a demonstration where, in the middle of a conversation, one of the participants swaps faces seamlessly. This video highlights how traditional authentication methods fail to detect such manipulations and showcases how Corsound AI’s technology—through voice-face matching and additional underlying biometric analysis—can reveal these face swaps in real time.

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The Solution: Multi-Modal Authentication

To combat these threats, organizations must adopt multi-modal biometric authentication, combining voice and face recognition along with deepfake detection technologies.

Corsound AI provides cutting-edge solutions that analyze both voice and face simultaneously, ensuring that the identity of a participant is legitimate and consistent across modalities.

By leveraging AI-powered deepfake detection and biometric fusion, businesses can stay ahead of fraudsters and secure their video communications from emerging threats.

As AI-driven deception grows more sophisticated, the only way to maintain trust in digital interactions is through a layered, intelligent approach to authentication.

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