Multi-layer Media Authentication via Blockchain Hash Verification
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Solution Overview
Problem
The rise of synthetic media, such as deepfakes, complicates user authentication by making it difficult for existing biometric mechanisms to distinguish between authentic and artificially produced media samples, leading to potential unauthorized access to secure information and services.
Innovation Solution
A multi-layer analysis system that decomposes media samples into separable code elements, generates hash values from critical portions, and compares these values to reference data stored in a blockchain ledger to verify user identity, effectively flagging synthetic media attempts as unauthorized.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional biometric authentication mechanisms are used, then user authentication can be performed, but the system becomes vulnerable to synthetic media attacks such as deepfakes
Solution Approach 1:
The patent divides the media sample into multiple separable layers (first layer, second layer, etc.), each containing specific code elements. This segmentation allows the system to analyze different aspects of the media independently and detect synthetic manipulations that may be hidden in specific layers. By comparing hash values of critical portions across multiple layers, the system can identify deepfake attacks that would pass single-layer analysis.
Solution Approach 2:
The patent transitions from traditional single-layer biometric comparison to multi-layer analysis, adding a dimensional aspect to authentication. Each layer represents a different dimension of media analysis, and the system requires consistent matching across all layers. This dimensional expansion makes it significantly harder for synthetic media to fool the system, as manipulating all layers consistently is computationally infeasible.
2Measurement precision
If multi-layer analysis with hash comparison is implemented, then authentication accuracy improves, but system complexity increases
Solution Approach 1:
The patent pre-computes and stores hash values of critical portions from authentic media samples in a blockchain ledger during the registration phase. This preliminary action allows the authentication system to simply compare newly generated hash values against stored reference values, rather than performing complex analysis during authentication. The blockchain ledger serves as a pre-prepared reference database, simplifying the authentication process while maintaining high accuracy.
Solution Approach 2:
The patent replaces traditional mechanical biometric comparison methods with cryptographic hash function-based verification. Instead of directly comparing media samples or using complex machine learning models, the system applies hash functions to critical portions and compares the resulting hash values. This substitution simplifies the authentication logic while dramatically improving accuracy in detecting synthetic media, as hash comparison is computationally efficient and highly sensitive to any modifications.
Data Source
AI summary
A system receives a login sample. The login sample is decomposed into first and second layers. A verification media sample is decomposed into first and second layers. The system determines that the first layer of the login sample does not match the first layer of the verification sample, that the second layer of the login sample does not match the second layer of the verification sample, or both. First and second critical portions are extracted from the login sample. A first and second login hash are generated from the first and second critical portions. A first and second ledger hash are retrieved from a blockchain ledger. It's determined that the first login hash does not match the first ledger hash, the second login hash does not match the second ledger hash, or both. The user is flagged.