Communication Trust Levels from Audio-Video Authentication
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Solution Overview
Problem
The challenge of trusting whether a real person or a deepfaked version is participating in audio and/or video conferences poses a security risk, making it difficult to authenticate participants effectively.
Innovation Solution
A communication system and method that determine a trust level for media streams based on audio and video data, using cryptographic keys, device signatures, and biometric data to provide real-time feedback on participant authenticity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional communication systems are used without trust verification, then the system is simple and easy to operate, but security is compromised and impersonation attacks succeed
Solution Approach 1:
The system performs preliminary authentication actions by verifying cryptographic signatures and biometric data before allowing media stream participation. Trust levels are determined in advance based on device signatures, cryptographic keys, and biometric verification, preventing impersonation attacks before they can succeed.
Solution Approach 2:
The system introduces an intermediary trust verification mechanism that acts as a mediator between communication parties. This intermediary layer analyzes cryptographic signatures, device identifiers, and biometric data to determine trust levels, adding security without requiring direct complex interactions between all participants.
2Reliability
If trust verification mechanisms are implemented, then impersonation attacks are reduced, but the system becomes more complex
Solution Approach 1:
The authentication system is segmented into distinct modular components: cryptographic signature verification, device signature validation, biometric data analysis, and trust level determination. Each component handles a specific aspect of verification, making the overall complex system manageable and maintainable through clear separation of concerns.
Solution Approach 2:
The system employs universal cryptographic mechanisms and standardized verification protocols that can be applied across different communication scenarios and platforms. The trust verification framework is designed to work with various types of media streams and communication devices, reducing complexity through reuse of established standards.
3Loss of information
If real-time trust level monitoring is provided, then participant authenticity awareness is improved, but processing requirements increase
Solution Approach 1:
The system performs partial verification by focusing on key authentication elements rather than analyzing every aspect of media streams in real-time. Trust levels are determined based on essential cryptographic and biometric factors, providing sufficient authenticity information without requiring exhaustive processing of all media data.
Solution Approach 2:
The system enables self-service authentication where devices automatically verify their own cryptographic signatures and biometric data without requiring extensive external processing. Each participant's device independently validates its own trust credentials, reducing the processing burden on the overall system while maintaining continuous authenticity monitoring.
Data Source
AI summary
An electronic device and a method of operating an electronic device comprising processor circuitry is disclosed, the method comprising receiving media data associated with a media stream, the media data comprising one or both of audio data representative of audio and video data representative of video; determining a trust level associated with the media stream based on the media data; and providing an output indicative of the trust level.