Video Clip Authentication via Embedded Frame Signatures
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Solution Overview
Problem
Advanced video editing techniques, such as Deepfake, make it difficult to detect modifications in digital videos, posing a threat to the credibility of recorded events, as users can easily manipulate content, and existing methods lack efficient tools for authenticating video integrity.
Innovation Solution
Embedding frame signatures within video clips by analyzing pixels to calculate features, such as faces or objects, and using hash functions to generate unique signatures that are embedded in background pixels, allowing for real-time authentication of video authenticity during playback without requiring pre-processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If sophisticated video editing techniques like Deepfake are used to manipulate content, then the ease of creating modified videos is improved, but the reliability of video authenticity deteriorates
Solution Approach 1:
The system embeds frame signatures into video frames during the initial encoding process, before the video is distributed or viewed. This preliminary action ensures that authenticity verification data is already in place, allowing detectors to verify video integrity without requiring re-encoding or complex preprocessing of the original source material.
Solution Approach 2:
The patent introduces frame signatures as an intermediary element that mediates between the video content and the authenticity verification process. These signatures act as a trusted intermediary that links the original video frames to their authentic source, enabling detectors to verify authenticity without directly analyzing the complex Deepfake manipulated content.
2Measurement precision
If frame signatures are embedded in every frame, then the measurement precision of modification detection is improved, but the device complexity increases
Solution Approach 1:
The system segments the video into individual frames and embeds signatures in each frame independently. This segmentation allows the detection process to work on a frame-by-frame basis, improving measurement precision for detecting modifications while keeping the complexity manageable by processing discrete, independent units rather than the entire video as a single complex object.
Solution Approach 2:
The patent changes the parameter of signature embedding from a single global signature to per-frame signatures with varying complexity. The system can adjust the signature length and embedding method based on the specific frame characteristics, optimizing the balance between detection precision and processing complexity for different video content.
3Reliability
If hash functions are used to generate unique signatures for each frame, then the reliability of authenticity verification is improved, but the loss of processing time increases
Solution Approach 1:
The hash functions generate frame signatures during the initial video encoding process, before the video is distributed or viewed. This preliminary computation of signatures eliminates the need for time-consuming hash calculations during playback or verification, as the signatures are already embedded in the video frames and can be directly compared for authenticity verification.
4Productivity
If signature verification is performed in real-time during playback, then the productivity of authentication is improved, but the device complexity increases
Solution Approach 1:
The system extracts only the embedded frame signature data from each video frame for verification purposes, rather than analyzing the entire frame content. This extraction approach enables real-time authentication during playback by comparing the extracted signature against the expected value, improving productivity while keeping the verification process simple and avoiding complex image analysis.
Data Source
AI summary
Techniques for digital video authentication (and preventing fake videos) are disclosed. First pixels within a first image frame of the video clip representing an area of interest within the first image frame may be identified. The area of interest may correspond to a person's face or another object. A first frame signature may be calculated based on the first pixels. Second pixels within a second image frame of the video clip representing an area of interest within the second image frame may be identified. A second hash value may be calculated based on the second pixels. The authenticity of the video clip may be determined by comparing the first and second hash values against data extracted from third pixels within the first image frame that do not correspond to the area of interest in the first image frame.