Distributed Data Store Segmentation for Sensitive Content Security
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Solution Overview
Problem
Enterprises face challenges in managing and securing unstructured and semi-structured data due to risks of data breaches, misuse of confidential information, and the need for effective data classification and access control, particularly from both internal and external threats.
Innovation Solution
A system and method for organizing and processing data using dynamic, adaptive filters that categorize and classify select content, employing content-based, contextual, and taxonomic filters to securely store and manage sensitive data, ensuring controlled release and distribution based on security clearances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in distributed data stores with multiple filters and classification systems, then data security and classification accuracy are improved, but system complexity and data access time increase
Solution Approach 1:
The patent segments data into different classification levels (confidential, internal, public) and stores them in separate distributed data stores. Each data store is managed by specific filters tailored to its classification level, allowing security to be improved through segmentation while managing complexity by organizing systems into modular, classification-based units.
Solution Approach 2:
The patent introduces intermediary components including a classification engine that automatically categorizes data before storage, and a data release control system that acts as a mediator between data requests and distributed data stores. These intermediaries handle the complex security and classification logic, shielding users from system complexity while maintaining high security standards.
2Measurement precision
If dynamic adaptive filters are used to classify and secure data, then classification accuracy and security are improved, but processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary classification of data upon ingestion into the system. The classification engine automatically analyzes and categorizes data before it enters the distributed storage system, assigning appropriate security labels and routing to relevant data stores. This preliminary action ensures high classification accuracy while avoiding repeated processing delays during data access operations.
Solution Approach 2:
The patent employs dynamic adaptive filters that can adjust their classification criteria based on data patterns, user roles, and security contexts. These filters learn from classification outcomes and refine their accuracy over time, improving measurement precision while optimizing processing time through adaptive decision-making that avoids unnecessary computational overhead for routine classifications.
3Reliability
If controlled release mechanisms with security clearances are implemented, then data protection and compliance are improved, but data distribution efficiency and accessibility decrease
Solution Approach 1:
The patent implements a feedback mechanism in the data release control system that tracks data access patterns, user roles, and security clearance levels. The system automatically adjusts release permissions based on accumulated feedback, granting access to authorized users without requiring manual security reviews for each request. This maintains strong data protection while improving distribution efficiency through automated, policy-based access decisions.
Solution Approach 2:
The patent creates a universal data release control system that handles multiple security requirements (confidentiality, integrity, availability, compliance) through a single integrated mechanism. The system evaluates user clearances, data classifications, and policy rules simultaneously to make comprehensive access decisions, improving data protection across multiple dimensions while maintaining distribution efficiency by avoiding multiple separate control processes.
Data Source
AI summary
Method and system of organizing and processing data in a distributed computing system having designated, distributed data stores for sensitive content (e.g., trade secrets) or select content (e.g., critical content). Sensitive/select data is extracted via configurable filters and stored in the designated data stores, sometimes subject to security controls, with limiting distribution functions and controlled release of the sensitive/select data. Distribution is limited due to designated, configurable filters.