Video Call Deepfake Prevention
Safeguard Calls, Protect Your Business with Deepfake Prevention
Combat the rising threat of deepfakes in video conferencing and ensure authentic communication.
The Rising Threat of Deepfakes in Video Calls
Fraudsters create deepfakes to impersonate key business individuals (executives, employees, or clients), and take advantage of people.
Facia's advanced technology safeguards your organisation from video stream manipulation during video call meetings, creating a trustworthy environment.
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AI-Powered Video Deepfake Detection
Facia uses advanced AI algorithms to detect and neutralise deepfakes in real time, safeguarding your video communication from manipulation. We analyze video streams for subtle inconsistencies that expose even the most sophisticated deepfakes.
- Multi-level Analysis
- Real-time Detection
- Advanced Anomaly Detection
In-depth Analysis with Emotion Recognition
Deepfakes find it really difficult to convincingly replicate human emotions. Real-time emotion analysis in video feeds can help to identify the subtle inconsistencies that would be otherwise overlooked.
Why Choose Facia?
At Facia, we believe in the power of responsible AI to foster genuine human connection in the digital age. Facia allows you to:
- Mitigate deep fake risks and protect your brand image.
- Get facial recognition for real-time attendee verification.
- Automatic face detection to enhance security measures.
Recent Examples of Deepfakes in Video Calls
Hong Kong CFO
A Hong Kong finance firm lost $25 million with a single transaction when scammers used a deepfake to impersonate the company's CEO during a Zoom meeting. The deepfake was so convincing it fooled an experienced worker, resulting in a huge financial loss.
CyberArk CEO
An employee used free online tools to create a shockingly realistic deepfake of their CEO: Udi Mokady. The deepfake, showing Mokady casually dressed within his office, was startlingly real, even fooling the CEO himself when revealed in a Teams message.
Binance CCO
Fraudsters exploited Hologram AI to create deepfakes of the Binance CCO, using a familiar face and behavior to build a false sense of security during video conferences. This tactic targeted unsuspecting victims within the crypto sphere.
Ready for a Secure, Deepfake-Free Video Call Experience?
Request A DemoFrequently Asked Questions
Deepfakes in live calls can be created using two main techniques:
Face Swapping with GANs: This involves training two neural networks against each other to create realistic deepfakes.
Deep Reinforcement Learning: AI agents learn to manipulate facial features in real-time for dynamic deepfakes.
Yes. Deepfakes can be used to disrupt or deceive in Zoom meetings just as easily as on other video conferencing platforms. They manipulate the video stream itself, making it difficult for platforms to detect. Attackers might impersonate participants or inject false information.
Here are some signs that might indicate a deepfake:
- Unnatural Facial Expressions: Pay attention to anything unusual, such as stiffness, lack of blinking, or misaligned facial features.
- Lighting Inconsistencies: Look for strange shadows, mismatched lighting between the face and the background, or flickering around the edges.
- Audio-Visual Discrepancies: Pay attention if the voice seems off, or there's a mismatch between lip movements and audio.
- Suspicious Behavior: The person says something out of character or the call feels unusual and odd.
Facia's proprietary AI technology, Morpheus, uses advanced deep learning models like Convolutional Neural Networks (CNNs) to analyse subtle variations that reveal deepfakes.
Additionally, Morpheus incorporates 3D liveness detection, examining biological markers (like eye movements) that are difficult for deepfakes to replicate.
