Entity Engine for Personal Identifier Detection
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Solution Overview
Problem
Current techniques for identifying data containing sensitive or confidential information in computing environments are not sufficiently accurate, leading to undetected data breaches and exfiltration attempts.
Innovation Solution
The implementation of an entity engine that classifies content into various content types using a set of predefined entity definitions, which include regular expressions, terms, and dictionary entries, to accurately identify personal identifiers and prevent data breach or exfiltration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If word-by-word or phrase-by-phrase comparison with a dictionary is used to identify sensitive information, then the identification process is simple and fast, but the accuracy is insufficient leading to false positives
Solution Approach 1:
The patent segments the identification process into multiple stages: first using simple dictionary comparison for rapid initial filtering, then applying contextual analysis and entity relationship verification to identified candidates. This multi-stage segmentation maintains speed while improving accuracy by only applying complex analysis where needed.
Solution Approach 2:
The patent introduces contextual information and entity relationship data as intermediary elements between the simple dictionary matching and the final identification decision. These intermediaries provide additional verification layers that reduce false positives without significantly impacting overall processing speed.
2Ease of operation
If simple dictionary comparison is used without context, then the system is easy to operate, but data breaches remain undetected due to inaccuracy
Solution Approach 1:
The patent performs preliminary actions by pre-processing and storing contextual information, entity definitions, and relationship data before the actual identification process. This preparation enables the system to quickly access relevant context during operation, maintaining simplicity while improving detection reliability.
Solution Approach 2:
The system enhances itself by automatically acquiring and utilizing contextual information from the computing environment without requiring manual configuration. The entity engine self-adapts to the specific environment, improving reliability while maintaining ease of operation through automated context acquisition.
3Measurement precision
If entity engine with predefined entity definitions is used to increase accuracy, then identification precision improves, but system complexity increases
Solution Approach 1:
The patent creates a universal entity engine that can handle multiple types of sensitive information (personal identifiers, financial data, health information, etc.) through a single unified framework. This multi-functionality reduces the need for separate specialized systems, managing complexity while maintaining high identification accuracy across different data types.
Solution Approach 2:
The patent manages complexity by making the entity definitions and parameters configurable and adaptable. The system can adjust the strictness of entity matching, the types of context considered, and the verification thresholds based on specific deployment requirements, allowing accuracy to be tuned without permanently increasing structural complexity.
Data Source
AI summary
Provided herein are systems and methods for identifying personal identifiers in content. An entity engine may receive content to identify candidate personal identifiers. The entity engine may determine that a text string in the content matches to a data format specified in entity definitions corresponding to types of personal identifiers and a rule for finding a geographic or linguistic term in the content correlated to the specific type of personal identifier. Each entity definition may specify a data format for finding a specific type of personal identifier in content. The data format corresponds to a type of personal identifier. The entity engine may identify, according to a rule of the first entity definition, a geographic or linguistic term in the content correlated to the type of personal identifier. The entity engine may classify the text string as the type of personal identifier, for preventing data breach or exfiltration.