Semantic Classification Signatures for Data Security
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Solution Overview
Problem
Current information systems with multi-level security architecture models face challenges in accurately determining and managing security classifications for data, leading to misclassification and unauthorized access due to manual tagging and lack of semantic analysis.
Innovation Solution
A method and apparatus for determining security classifications using a semantic engine to generate and compare classification signatures based on semantic interpretations of data, ensuring matching security classifications and providing real-time monitoring and recommendations for data modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tagging and keyword search are used for security classification, then the system is simple to implement, but the classification accuracy is low leading to misclassification
Solution Approach 1:
The patent replaces manual tagging and keyword-based classification (mechanical/simple systems) with semantic analysis using natural language processing and machine learning models. The semantic engine analyzes the meaning, context, and relationships of words and phrases in data to determine appropriate security classifications, thereby improving accuracy while accepting increased system complexity through automated intelligent processing.
2Measurement precision
If semantic analysis is implemented for automated classification, then classification accuracy improves, but processing time increases
Solution Approach 1:
The patent implements preliminary action by pre-processing and indexing semantic features of data during ingestion or storage phases. The semantic engine analyzes and extracts meaningful patterns, entities, and relationships in advance, creating structured representations that can be quickly queried and classified later. This reduces processing time during actual classification operations while maintaining high accuracy through pre-computed semantic understanding.
3Adaptability or versatility
If users are given access to multiple security compartments, then operational flexibility increases, but the risk of information aggregation and unauthorized access increases
Solution Approach 1:
The patent implements feedback mechanisms through real-time semantic analysis of user access patterns and data classification. The system continuously monitors and analyzes the semantic relationships between data in different compartments, detecting potential information aggregation risks. When unauthorized access patterns or misclassifications are detected, the system provides feedback to automatically adjust access controls, alert administrators, or reclassify data, thereby maintaining operational flexibility while mitigating security risks through continuous intelligent monitoring.
Data Source
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AI summary
Disclosed herein is a method for determining a security classification for data that includes generating a classification signature for data based on a semantic interpretation of the data. The classification signature is associated with a security classification for the data. The method also includes comparing the generated classification signature to a predetermined classification signature associated with the security classification. Further, the method includes verifying the generated classification signature matches the predetermined classification signature.