Traceable Document Variations via NLP Text Segmentation
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Solution Overview
Problem
Organizations face challenges in protecting confidential documents from unauthorized disclosure, despite using secure distribution systems and confidentiality agreements, as there is still a risk of leaks due to the ease of sharing digital information.
Innovation Solution
Generating subtly different variations of documents using natural language processing (NLP) to create traceable copies, which can be distributed to different recipients, allowing for tracking of the document's recipient based on the variations included in each copy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If confidential documents are distributed in digital form for convenience, then ease of operation is improved, but security against unauthorized disclosure deteriorates
Solution Approach 1:
The document is segmented into multiple unique copies, each distributed to different recipients. This segmentation allows the system to maintain ease of digital distribution while enhancing security through traceability of each segment to its recipient.
Solution Approach 2:
The patent applies textual variations (analogous to color changes) by modifying punctuation, capitalization, and formatting in each document copy. These subtle visual changes make each copy unique and traceable while maintaining the same underlying information, thus preserving security without compromising distribution ease.
2Stability of the object's composition
If identical document copies are distributed to multiple recipients, then consistency of information is improved, but ability to trace unauthorized disclosure deteriorates
Solution Approach 1:
The patent applies local quality by making only specific local modifications to each document copy (such as changing punctuation in certain sentences or capitalization of specific words). This allows the core information to remain consistent across all copies while introducing unique identifiable characteristics in localized areas for traceability.
Solution Approach 2:
The system changes textual parameters (punctuation marks, capitalization, spacing, formatting) in each document copy. These parameter changes create unique variations that maintain information consistency at the semantic level while enabling traceability at the syntactic level.
3Difficulty of detecting and measuring
If document variations are created using NLP processing, then traceability is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary NLP processing system that automatically generates text variations. This intermediary handles the complexity of creating traceable document variations, transforming the simple input of a base document into multiple traceable copies without requiring the end-user system to become complex.
Solution Approach 2:
The system creates multiple copies of the document with automated textual variations. By using copying combined with NLP-based parameter changes, the system achieves traceability without manually creating each variation, thus managing complexity through automation rather than manual processes.
Data Source
AI summary
In some embodiments, a method includes: generating, by the computing device, different variations of text based on a source document, the different variations to convey the same meaning as the source document while including content different than that of the source document; generating, by the computing device, copies of the document that include at least one of the different variations of the text, so that individual copies of the document are traceable based on the different variation of the text included within that copy of the document; and determining, by the computing device, a recipient of a copy of the document based on a different variation of the text included with the copy.