Facial Landmark Watermarking for Deepfake Traceability
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Solution Overview
Problem
Current Deepfake detection methods rely on passive detection, which cannot prevent the generation and propagation of deepfakes, and lack the ability to generate unique watermarks for each individual, thereby failing to achieve traceability.
Innovation Solution
An active-defense detection method based on facial landmark watermarking is introduced, which involves acquiring and preprocessing facial images, extracting facial landmarks, constructing an encoder and decoder, and embedding watermarks into images to enable traceability and detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If passive detection methods are used to detect deepfakes, then detection capability is provided, but prevention capability and traceability are lost
Solution Approach 1:
The patent applies preliminary action by embedding watermarks into facial images before they are potentially deepfaked. The watermark embedding occurs during the image processing stage, allowing subsequent active detection and tracing of deepfake attempts before they can cause harm. This proactive approach transforms the system from reactive passive detection to preventive active defense.
Solution Approach 2:
The patent implements feedback mechanisms through the encoder-decoder architecture that processes watermarked images and generates detection results. The system continuously learns from detected deepfake patterns and adjusts its detection thresholds, creating a closed-loop system that improves reliability over time while maintaining prevention and traceability capabilities.
2Measurement precision
If semi-fragile watermarks are used, then authenticity detection is enabled, but traceability function is lost
Solution Approach 1:
The patent applies universality by designing a watermark system that simultaneously performs multiple functions: authenticity verification, source identification, and traceability. The watermark structure encodes both verification data and traceable identifiers, allowing a single watermark mechanism to fulfill multiple protective roles without requiring separate systems.
Solution Approach 2:
The patent uses composite materials by combining multiple types of information within the watermark structure itself. The watermark integrates authenticity verification data, source identification codes, and traceability markers into a unified composite signal that can be processed together through the encoder-decoder system, enabling simultaneous execution of multiple detection functions.
3Stability of the object's composition
If robust watermarks with random or fixed patterns are used, then detection stability is improved, but individual uniqueness and traceability are compromised
Solution Approach 1:
The patent applies local quality by making each watermark individually customized based on the specific facial image characteristics. Instead of using uniform random or fixed watermarks across all images, the system generates unique watermarks tailored to each image's local features, ensuring both stability in detection and uniqueness for traceability purposes.
Solution Approach 2:
The patent implements dynamics by making the watermark adaptive to the specific image being watermarked. The watermark generation process dynamically adjusts parameters based on the input image characteristics, creating a flexible system that maintains stability through consistent detection methodology while achieving uniqueness through image-specific customization.
Data Source
AI summary
An active-defense detection method based on facial landmark watermarking is provided. The active-defense detection method includes: extracting facial landmarks from an original image, converting the extracted facial landmarks into a binary watermark, embedding the binary watermark into the original image to form a watermark image, and subjecting the watermark image to a non-malicious/malicious operation to form a noise image or a malicious image such that a model is robust to the non-malicious/malicious operation. By introducing the facial landmarks, the active-defense detection method can generate a unique watermark for each individual and achieve traceability and detection functions.