Data Tracking Database for Unauthorized Release Detection
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Solution Overview
Problem
Large organizations face challenges in identifying the source of unauthorized data releases due to their inability to determine which external entities had access to sensitive data, as current systems are not practical for managing and searching large volumes of shared documents for relevant characteristics.
Innovation Solution
A computer system that tracks data shared with external entities by storing select characteristics in a database, allowing for easy searching and identification of external entities that may have been sources of unauthorized data releases, without the need to save copies of all shared information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If organizations save copies of all shared documents to track data, then data tracking capability is improved, but storage requirements and system complexity increase significantly
Solution Approach 1:
The patent extracts only the necessary characteristics (data type, sensitivity level, sharing date, recipient entity) from the full documents and stores these metadata in the database. This allows tracking capability without storing complete document copies, thereby reducing storage requirements and system complexity while maintaining effective data tracking.
Solution Approach 2:
The patent creates a simplified copy of only the essential characteristics rather than copying the entire document. This selective copying approach enables the system to track data sharing information without the burden of storing full document contents, resolving the contradiction between tracking capability and system complexity.
2Measurement precision
If organizations search through large volumes of shared documents to identify unauthorized releases, then detection accuracy is improved, but search time and operational efficiency deteriorate
Solution Approach 1:
The patent segments the data sharing information into discrete, indexed characteristics (data type, sensitivity level, sharing date, recipient entity). This segmentation allows the system to quickly query and filter records based on specific criteria without searching through entire documents, thereby improving search efficiency while maintaining detection accuracy.
Solution Approach 2:
The patent performs preliminary action by pre-indexing and organizing data sharing characteristics in the database before unauthorized releases occur. This preliminary organization enables rapid searches and identifications when issues arise, eliminating the need to search through large volumes of documents in real-time and thus improving both detection accuracy and search efficiency.
3Reliability
If organizations maintain detailed records of all data sharing, then data security management is improved, but time required for compliance reporting and investigations increases
Solution Approach 1:
The patent extracts only the essential data sharing characteristics needed for security management and compliance (data type, sensitivity, date, recipient) and stores these in an organized database structure. This extraction approach provides sufficient information for effective security management and compliance reporting without requiring time-consuming reviews of complete documents, thus improving reliability while reducing time requirements.
Solution Approach 2:
The patent performs preliminary action by pre-organizing data sharing records in a structured database with appropriate indexing and categorization. This preliminary organization enables rapid retrieval and reporting when compliance issues arise, eliminating the need to search through unorganized records and thereby improving data security management effectiveness while reducing compliance reporting time.
Data Source
AI summary
System and method for keeping inventories of sensitive data that has been shared with external entities. The system and method may be used particularly for identifying a source of an unauthorized release of sensitive data.