PDF Code Analysis for Document Authenticity

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Solution Overview

Problem

Existing methods for determining the authenticity of digital documents, such as PDFs, are limited by their reliance on image analysis, which can incorrectly flag legitimate annotations as fraudulent and fail to detect tampering not visible in the rendered image.

Innovation Solution

An automated process that analyzes the PDF code of digital-origin documents to determine authenticity, using detectors that compare target document features against a sample set of legitimate documents within the same class, generating feature-specific anomaly scores that are combined to produce a document anomaly score.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If image analysis is used to detect document authenticity, then visible fraud indicators can be detected, but legitimate annotations are incorrectly flagged as fraudulent

Engineering Contradiction:

Improvefraud detection accuracyVSAvoidfalse positive rate

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent extracts and analyzes the underlying PDF code structure separate from the rendered image. By examining the code layer directly, the system can distinguish between legitimate annotations (properly coded in PDF) and fraudulent alterations (code inconsistencies), eliminating false positives while maintaining fraud detection accuracy.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent transitions from two-dimensional image analysis to analyzing the structured code dimension of PDF documents. This additional dimension reveals metadata, font information, and structural properties that are invisible in rendered images, enabling accurate distinction between legitimate and fraudulent modifications.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Ease of manufacture

If image analysis is used to detect document authenticity, then the process is simple to implement, but tampering not visible in the rendered image cannot be detected

Engineering Contradiction:

Improveimplementation simplicityVSAvoidtamper detection capability

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent uses PDF code structure and metadata as an intermediary layer between the visible document and the detection system. This intermediary contains hidden information about document creation, modifications, and structural integrity that reveals tampering invisible in rendered images, enhancing detection precision without significantly complicating implementation.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Reliability

If PDF code analysis is used instead of image analysis, then legitimate and fraudulent annotations can be distinguished, but the analysis process becomes more complex

Engineering Contradiction:

Improveannotation verification accuracyVSAvoidanalysis process complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the PDF analysis into distinct components: metadata examination, font analysis, structural validation, and annotation verification. Each segment can be independently processed and evaluated, making the overall complex analysis process more manageable and implementable through modular detection systems.

Inventive Principle:

Principle #1Segmentation

4Productivity

If image analysis is used for fraud detection, then processing speed is fast, but human review is still required for flagged documents

Engineering Contradiction:

Improveinitial screening speedVSAvoidhuman review time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent replaces the mechanical image analysis system with an automated code analysis system that provides more reliable results. By analyzing the structured PDF code rather than rendered images, the system achieves higher accuracy that reduces false positives, thereby minimizing the need for human review and reducing time loss while maintaining fast automated processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250053673A1Automated Fraudulent Document Detection

Publication Date: 2025.02.13 LENDINGCLUB BANK NAT ASSOC

AI summary

Techniques are disclosed for determining the authenticity of a digital-origin document based, at least in part, on the code of the document. By determining authenticity based on the code of the document, authentication may take into account several features that are not detectable on the rendered image of a digital-origin document. The document class of a target document is initially determined. Anomalies are then detected in the code using various detectors, including but not limited to metadata-based detectors and content-based detectors. The output of the detectors may be combined to generate a document anomaly score that indicates likelihood that the document is not authentic.