Document Watermark Detection for Fragmented Leak Source Identification
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Solution Overview
Problem
Existing systems for managing private documents lack robust methods to identify the source of document leaks, especially when the recovered artifact is a fragment or a different type from the original, and are susceptible to formatting changes, resizing, and perspective distortions.
Innovation Solution
Generate unique copies of a document with subtle perturbations, align artifacts with these copies using keypoints, and compare pixel regions to identify the source, employing computer vision techniques to correct for distortions and resizing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional document leak detection methods are used, then the system can identify sources of leaks, but the methods fail when the leaked artifact is a fragment or differs in format from the original and are susceptible to distortions and changes in document formatting, size, and quality
Solution Approach 1:
The patent segments the document comparison task into multiple independent components: generating unique perturbations for different document regions, extracting keypoints from both original and leaked documents, and comparing corresponding regions separately. This segmentation allows the system to handle fragmented artifacts by comparing only the overlapping regions while maintaining overall detection accuracy.
Solution Approach 2:
The patent applies local quality by making different parts of the document have different identifiable characteristics through unique perturbations. Each region or element in the original document is modified with distinct perturbations (such as unique spacing changes, font variations, or formatting differences), enabling the system to identify which specific region in a leaked fragment corresponds to which region in the original document, even when the artifact is distorted or fragmented.
2Measurement precision
If the system compares entire documents to identify leaks, then comprehensive comparison is achieved, but computational resources are wasted when only small fragments are leaked or when documents are large
Solution Approach 1:
The patent extracts only the necessary components for comparison: unique perturbations from the original document and corresponding keypoints from the leaked artifact. By extracting and comparing only these essential features rather than entire documents, the system achieves accurate identification while significantly reducing computational resource consumption, especially when dealing with fragmented leaks or large documents.
Solution Approach 2:
The patent applies partial action by performing comparison operations only on the portions of documents that are necessary for identification. When a leaked artifact is a fragment, the system compares only the corresponding region from the original document rather than the entire document. This partial comparison approach maintains identification accuracy while avoiding the waste of computational resources on irrelevant portions.
3Measurement precision
If the system uses detailed perturbation analysis to identify unique copies, then accuracy in identifying the source of leaks is improved, but the complexity of the detection system increases
Solution Approach 1:
The patent applies preliminary action by pre-generating unique perturbations and embedding them into the original document before the leak occurs. These perturbations (such as unique spacing patterns, font variations, or formatting characteristics) are prepared in advance and stored as reference data. When a leak is detected, the system only needs to compare the leaked artifact against these pre-prepared perturbations, simplifying the detection process while maintaining high accuracy.
Data Source
AI summary
Document source detection uses unique copies to identify sources of leaked documents. The unique copies are generated from an original document and include a unique watermarking of one or more perturbations to a feature of the original document. An artifact, such as a photo or copy, is derived from one of the unique copies, the unique copy from which it was derived is identified. To identify the unique copy, unique copy keypoints in the unique copies are matched to artifact keypoints in the artifact to align the artifact with a location within the unique documents. Pixel regions in the unique copies that include perturbations are used to identify corresponding pixel regions in the artifact. Pixels in these regions are compared to identify the unique copy from which the artifact was derived, thus identifying a possible source of the leaked document.