Security Labeling Service Dynamic Access Control
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Solution Overview
Problem
Existing methods for managing sensitive data, such as medical records, face challenges in enforcing access restrictions and compliance with changing jurisdictional laws, as they require maintaining separate databases and recompiling access rights, which is costly and introduces downtime.
Innovation Solution
A Security Labeling Service (SLS) that tags electronic records or data streams with security labels at runtime, using a rule generation service, extraction engine, and transformation engine to apply authorization, organizational policy, and government regulation constraints, ensuring automated compliance and enforcement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If separate databases are maintained for different versions of data with different access privileges, then access control is improved, but system complexity and cost increase
Solution Approach 1:
The patent segments access control into two independent layers: a single unified database for data storage and a separate rule set layer for access control policies. This allows access control to be enforced without duplicating data across multiple databases, reducing system complexity while maintaining reliability.
Solution Approach 2:
The patent introduces an intermediary component (the rule set and policy engine) that sits between the unified database and access requests. This intermediary handles all access control logic, allowing the database to remain simple and unified while still providing reliable access control through the mediating rule evaluation process.
2Reliability
If databases are recompiled when access rights change, then access control is updated, but downtime and operational disruption increase
Solution Approach 1:
The patent implements dynamic access control where the rule set can be modified and updated without requiring database recompilation or system downtime. The policy engine evaluates rules in real-time, allowing access rights to change dynamically while the system remains operational, eliminating the downtime associated with traditional database recompilation approaches.
Solution Approach 2:
The patent performs preliminary organization of access control rules into a separate, pre-compiled rule set structure that can be efficiently evaluated without touching the database. When access rights change, only the rule set needs updating rather than the entire database, allowing for faster updates with minimal operational disruption.
3Reliability
If separate databases are maintained for different access versions, then access control is improved, but operational cost increases
Solution Approach 1:
The patent merges all data into a single unified database while separating access control logic into an independent rule set. This consolidation eliminates the need to maintain and synchronize multiple separate databases, reducing storage costs, maintenance overhead, and operational expenses while preserving access control functionality through the unified rule-based approach.
Solution Approach 2:
The patent creates a universal rule set that can enforce different access control policies across the entire database without requiring separate database instances. This multi-functional rule engine can handle various access scenarios (different users, different data types, different time periods) within a single system, reducing the operational costs associated with maintaining multiple specialized databases.
Data Source
AI summary
The disclosure comprises a method, an apparatus, and instructions for controlling a computer to implement a security labeling service (SLS) to tag an electronic record or data stream with security labels to ensure compliance with access restriction requirements. The SLS tags a record or data stream with security labels according to constraints including jurisdictional (government regulation), organizational policy, and authorization of a subject of record (e.g. patient consent). The SLS consumes a vocabulary dictionary to interpret the record and the constraints to generate rules for tagging the data. The original record or data stream is then tagged according to the rules. The tagged output is used to ensure compliance with the security labels.