Fakeradar

Product Introduction

1. FakeRadar.io is a real-time deepfake detection tool designed to identify manipulated video content during live interactions such as video calls and meetings. It analyzes video streams instantly to determine whether the person on screen is authentic or a deepfake, using visual signals without accessing audio or stored files. The tool integrates with popular platforms like Zoom and Microsoft Teams, operating as a lightweight application that requires no recordings or delays.
2. The core value of FakeRadar lies in its ability to mitigate risks associated with identity spoofing, fraud, and social engineering by providing immediate verification of video authenticity. It empowers users to trust live interactions in critical scenarios such as remote interviews, financial transactions, and meetings with strangers. By focusing solely on visual data, it ensures privacy compliance while maintaining real-time performance.

Main Features

1. FakeRadar performs real-time video analysis by scanning live video frames for signs of deepfake manipulation, such as face swaps or unnatural facial movements, without requiring API access to video conferencing platforms. The tool processes visuals locally before sending encrypted frame data to its servers for immediate analysis, ensuring minimal latency.
2. The tool operates exclusively on visual inputs, avoiding microphone access or file uploads, which reduces privacy concerns and resource usage. It detects anomalies in facial expressions, eye movements, and texture inconsistencies using proprietary algorithms trained on diverse deepfake datasets.
3. FakeRadar supports on-premise deployment for enterprises requiring full control over data flow, enabling organizations to host the detection infrastructure internally. This feature caters to industries with strict compliance needs, such as finance and government, while maintaining the same real-time detection capabilities as the cloud version.

Problems Solved

1. FakeRadar addresses the growing threat of deepfake-driven fraud in live video interactions, where malicious actors impersonate individuals to manipulate outcomes in interviews, financial transactions, or confidential meetings. It eliminates blind trust in video-based communication by providing technical verification.
2. The primary target users include HR teams conducting remote hiring, financial institutions verifying client identities, and individuals engaging in video calls with strangers via platforms like telehealth or online marketplaces. Enterprises with high-security requirements, such as legal firms and government agencies, also benefit from its on-premise deployment.
3. Typical use cases include detecting AI-generated candidates during job interviews, preventing deepfake-based social engineering attacks in banking, and ensuring the authenticity of participants in sensitive corporate negotiations. It also serves individuals using dating apps or rental platforms to verify unknown contacts.

Unique Advantages

1. Unlike competitors that rely on post-call analysis or audio-video synchronization checks, FakeRadar specializes in real-time visual-only detection, which reduces false positives caused by network latency or audio artifacts. This approach ensures immediate feedback without disrupting conversation flow.
2. The tool’s on-premise deployment option and lack of audio/data storage differentiate it from cloud-only solutions, addressing privacy regulations like GDPR and CCPA. Its proprietary detection model updates dynamically to counter evolving deepfake techniques, using federated learning to improve accuracy without compromising user data.
3. Competitive advantages include seamless integration with any video platform via screen capture technology, eliminating dependency on API partnerships. The tiered pricing model (free to enterprise) scales for casual users and large organizations, while the confidence-label system (“authentic” or “potential fake”) simplifies decision-making for non-technical users.

Frequently Asked Questions (FAQ)

1. How does FakeRadar work without accessing my microphone or video platform APIs? FakeRadar uses screen capture technology to analyze video output displayed during calls, requiring no direct integration with conferencing tools. It extracts visual frames, encrypts them for server-side processing, and returns results within milliseconds, leaving no residual data.
2. What video platforms does FakeRadar support? The tool works with any video service, including Zoom, Microsoft Teams, Google Meet, and custom platforms, as it operates independently via screen capture. No additional software configuration is needed beyond installing the FakeRadar app.
3. How does the pricing model correlate with “checks”? A “check” refers to each real-time scan of a video stream during a call session. The free tier allows 50 monthly checks (e.g., 50 short calls), while enterprise plans offer unlimited scans. Checks are deducted per minute of continuous analysis, with granular usage tracking in the dashboard.
4. Does FakeRadar store or transmit my video data? No video or audio data is stored or transmitted beyond the encrypted frame analysis required for real-time detection. The system discards frame data immediately after generating a confidence score, ensuring compliance with data minimization principles.
5. Can FakeRadar detect all types of deepfakes? The tool focuses on face swaps and synthetic facial movements common in real-time deepfakes, achieving 98.7% accuracy in controlled tests. However, highly sophisticated pre-recorded deepfakes may require additional forensic analysis beyond FakeRadar’s real-time scope.