Dynamic Natural Language Steganography for Cloud Document Security
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Solution Overview
Problem
Legacy techniques for securing shared documents in cloud-based systems fail to effectively deter unauthorized disclosure and identify the source of leaked content, as they lack the ability to track unauthorized dissemination and are easily defeated by modifications such as retyping or screen capturing.
Innovation Solution
Implementing dynamic natural language steganography by injecting steganographic information into shared content using natural language processing, allowing for the identification of the source of unauthorized disclosure by recovering and analyzing the embedded message from modified content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If legacy watermarking techniques are applied to documents, then security indication and authenticity are improved, but the ability to track unauthorized dissemination source deteriorates
Solution Approach 1:
The patent segments the watermarking approach by creating multiple unique watermarks for different users rather than using a single uniform watermark. Each user receives a watermarked copy with their specific identifier embedded, allowing the system to segment and trace the source of any unauthorized dissemination to the specific user who received that particular watermarked version.
Solution Approach 2:
The patent applies local quality by making each watermark unique to its recipient rather than uniform across all copies. Each user's watermarked copy contains locally specific identification information (such as user ID, timestamp, or device identifier) that enables precise source attribution when that specific copy is leaked, while other watermarked copies remain unaffected.
2Measurement precision
If fixed algorithms are used for natural language processing watermarking, then text changes can be detected, but the ability to determine download source deteriorates
Solution Approach 1:
The patent transforms the static, fixed watermarking algorithm into a dynamic system where the watermarking parameters change based on the user and context. Instead of applying the same fixed transformations to all users, the system dynamically generates unique watermarking patterns for each user session, incorporating variables such as user identifier, timestamp, and session information, thereby enabling source identification while maintaining text change detection capability.
Solution Approach 2:
The patent changes the parameters of the watermarking process by introducing user-specific variables into the algorithm. Rather than using fixed transformation rules, the system modifies parameters such as the magnitude and direction of text changes based on user identity and session data, allowing the same base algorithm to produce unique, traceable watermarks for different users without requiring multiple fixed algorithms.
3Ease of manufacture
If uniform watermarking is applied to all users, then implementation simplicity is improved, but the ability to identify leak source deteriorates
Solution Approach 1:
The patent achieves universality by creating a single watermarking system that serves multiple functions: it maintains the simplicity of automated application while simultaneously embedding user-specific identification data. The same watermarking process is used for all users, but it dynamically adapts to incorporate their unique identifiers, thus providing both ease of implementation and source identification capability through a unified multi-functional approach.
Data Source
AI summary
Systems for secure cloud-based collaboration over shared objects. Embodiments operate within systems in a cloud-based environment, wherein one or more servers are configured to interface with storage devices that store objects accessible by one or more users. A process receives an electronic message comprising a user request to access an object. Before providing user access to the object, the system generates a requestor-specific steganographic message that is derived from some portion of requestor identification information and/or other user attributes, and/or object storage parameters. Various forms of a requestor-specific steganographic message are applied to selected portions of the object to generate a requestor-specific protected object, which is then provided to the requestor. A web crawler can identify posted unauthorized protected object disclosures. Using quantitative calculations and/or heuristics together with requestor-specific aspects of the embedded steganographic message, the source of the unauthorized disclosure can be identified.