Trusted Download Toolkit Automates Unclassified Data Extraction
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Solution Overview
Problem
Manual identification and separation of unclassified data from a mixture of classified and unclassified data in systems, programs, databases, or computer files is resource-intensive and impractical, requiring significant human effort and classified network access.
Innovation Solution
A method and apparatus using plain text format files with attributes to identify and extract unclassified data from a collection of both classified and unclassified data, employing a software tool called the Trusted Download Toolkit (TDT) that dynamically decodes and filters classified binary data based on system data description documentation, allowing for automated separation and transfer to an unclassified environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review is used to identify unclassified data, then data classification accuracy is improved, but resource consumption and time requirements increase significantly
Solution Approach 1:
The patent replaces the manual mechanical review process with an automated software system (TDT) that uses algorithms to identify and extract unclassified data. This substitution eliminates the need for human reviewers to manually examine each data element, dramatically reducing resource consumption while maintaining classification accuracy through systematic automated analysis of data attributes and metadata.
Solution Approach 2:
The system enables data to be automatically classified and extracted without human intervention. The TDT tool self-services by autonomously analyzing data collections, applying classification rules, identifying unclassified portions, and extracting them for transfer to unclassified environments, thereby eliminating the need for continuous manual resource allocation.
2Reliability
If all data is kept on a classified network, then security control is improved, but system complexity and access requirements increase
Solution Approach 1:
The patent extracts unclassified data from classified networks using the TDT tool, separating it into unclassified environments where it can be processed without classified access requirements. This extraction maintains security control by keeping classified data on the classified network while removing only the unclassified portions, thereby reducing system complexity and access requirements without compromising security.
3Reliability
If manual Trusted Download process is used, then data security is improved, but processing speed and efficiency decrease
Solution Approach 1:
The TDT tool performs preliminary automated analysis and classification of data before transfer, identifying unclassified portions in advance. This preliminary action maintains security by ensuring proper classification verification while dramatically increasing processing speed by eliminating the need for manual review of each data element during the transfer process.
Solution Approach 2:
The patent replaces the manual Trusted Download process with an automated system that uses software algorithms to perform classification verification and data extraction. This substitution maintains the security controls inherent in the Trusted Download process while increasing processing speed by automating the identification and extraction of unclassified data without human intervention.
Data Source
AI summary
A method of extracting unclassified data from a collection of data including both classified data and unclassified data, includes: providing a plain text format file including a plurality of attributes; using the attributes to identify unclassified data within a collection of data that includes a combination of unclassified and classified data; and extracting the identified unclassified data from the collection of data. An apparatus that implements the method is also provided.