Dynamic Digital Content Change Detection via Segmented Hashing
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Solution Overview
Problem
Conventional eDiscovery systems fail to effectively detect changes in dynamic digital documents that include links to other digital content, as they only consider static content and do not account for changes in linked or embedded data, leading to misleading results.
Innovation Solution
A method and system that calculate hash values for both static and dynamic content, including HTML files and linked content, to generate unique identifiers for digital content at different time periods, enabling detection of changes by comparing these identifiers over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional eDiscovery systems use static content identification methods, then the system complexity remains low, but the ability to detect changes in dynamic digital documents deteriorates
Solution Approach 1:
The patent segments digital documents into multiple components including static content, dynamic content, embedded objects, and linked content. Each segment is independently identified and hashed, allowing the system to track changes in specific portions while maintaining overall document integrity verification. This segmentation enables reliable change detection without requiring complete re-analysis of entire document ecosystems.
Solution Approach 2:
The patent introduces a temporal dimension to content identification by capturing document states at different points in time and comparing their unique identifiers. This time-based dimensionality allows the system to detect changes in dynamic content by comparing hash values across temporal snapshots, transforming a static identification problem into a dynamic change-detection solution.
2Measurement precision
If conventional systems only hash static document content, then the processing speed remains high, but the measurement precision of content changes deteriorates
Solution Approach 1:
By segmenting documents into static and dynamic components, the system applies appropriate hashing strategies to each segment. Static content is hashed once and stored, while dynamic content is hashed and compared across time periods. This segmentation enables precise change detection in dynamic portions without requiring re-processing of unchanged static portions, maintaining processing efficiency.
Solution Approach 2:
The patent extracts and separately processes dynamic content elements (embedded objects, linked content, metadata) from the main document body. By taking out these volatile elements for separate identification and comparison, the system achieves precise change detection in the extracted components while avoiding redundant processing of the remaining static document content.
3Reliability
If conventional eDiscovery systems do not account for linked content, then the ease of operation remains high, but the reliability of content integrity verification deteriorates
Solution Approach 1:
The patent implements a universal identification mechanism that handles multiple content types (static text, dynamic content, embedded objects, linked resources) through a unified hashing approach. This multi-functional system automatically detects and hashes all content types regardless of their nature or location, providing comprehensive integrity verification without requiring users to manually configure different verification methods for different content types.
Solution Approach 2:
The system automatically identifies and processes linked content and embedded objects without requiring user intervention. It self-service by recursively following links, extracting embedded content, and incorporating these elements into the overall document hash calculation, thereby maintaining reliability while preserving ease of operation.
Data Source
AI summary
Systems and methods provide for the collection of content, such as webpage content, and for detection of changes in content. Files composing a document at a different time periods may be accessed and sets of hash values corresponding to files composing the document at the different periods may be calculated. A determination is made as to whether a file in the identified files at the different time periods is an HTML file, and if so an additional hash value corresponding to the HTML file is calculated. Aggregated hash values may be calculated based on hash values in the sets of hash values. A report may be generated reporting hash values for the document as it exists at the different time periods, including the hash values for the files composing the document, the additional hash values for respective HTML files, and the aggregated hash values. Changes in hash values may be indicated.