Query Transformer Annotations for Multi-Domain Encryption Access
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Solution Overview
Problem
The complexity and inefficiency of managing different encryption mechanisms across multiple physical locations for data processing, particularly in client-server communication, lead to errors and reduced efficiency in data processing, compromising security and complicating data-analyst tasks.
Innovation Solution
A transformer module that analyzes client queries, identifies appropriate encryption mechanisms, and adds security-specific annotations, allowing seamless data access and processing across different domains and schemes, using a lattice-based security policy to ensure compatibility and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If different encryption mechanisms are used for different data, then security is improved, but device complexity increases and ease of operation deteriorates
Solution Approach 1:
The patent introduces a transformer module as an intermediary component between the query interface and the data storage system. This transformer automatically selects and applies appropriate encryption mechanisms based on data sensitivity labels, eliminating the need for users to manually manage multiple encryption schemes. The transformer acts as a mediator that handles the complexity of encryption mechanism selection and application, thereby improving security while maintaining ease of operation.
Solution Approach 2:
The system dynamically changes encryption parameters based on data sensitivity labels. Different data elements are assigned different sensitivity levels (e.g., public, internal, confidential, restricted), and the encryption mechanism automatically adjusts its parameters accordingly. This allows the system to apply stronger encryption only where necessary, improving overall security posture while avoiding the complexity of uniformly applying maximum encryption to all data.
2Reliability
If all data is encrypted according to the highest standard, then security is improved, but productivity decreases due to increased complexity and processing overhead
Solution Approach 1:
The patent implements local quality by applying different encryption standards to different data elements based on their specific sensitivity requirements. Rather than uniformly encrypting all data with the highest standard, the system assigns encryption levels locally to each data element according to its sensitivity label. This selective approach maintains high security for sensitive data while reducing processing overhead for less sensitive data, thereby improving overall productivity.
Solution Approach 2:
The system applies partial encryption action by encrypting only the portions of data that require protection based on their sensitivity labels. Not all data needs maximum encryption strength - the system applies encryption selectively and proportionally to the actual security needs of each data element. This partial action approach avoids the excessive processing overhead of encrypting everything at maximum strength while still providing adequate security where needed.
3Reliability
If encryption mechanisms are differentiated for different data types, then security is improved, but ease of operation deteriorates as data-analysts must account for multiple mechanisms
Solution Approach 1:
The transformer module implements self-service by automatically selecting and applying the appropriate encryption mechanism based on the sensitivity labels of the data being accessed. Data analysts no longer need to manually determine which encryption scheme to use - the system autonomously handles this decision-making process. The transformer examines the query, identifies the sensitivity requirements of the target data, and automatically applies the correct encryption mechanism, thereby maintaining security while dramatically improving ease of operation.
Solution Approach 2:
The transformer serves as an intermediary layer between the simple query interface and the complex encryption infrastructure. Data analysts formulate straightforward queries without needing to understand or specify encryption details. The transformer mediates between these simple queries and the underlying encryption mechanisms, automatically translating user intent into appropriately encrypted data access operations. This intermediary layer shields users from encryption complexity while ensuring security requirements are met.
4Productivity
If data is accessed across networks from different physical locations, then productivity is improved through distributed processing, but security risks increase due to transmission vulnerabilities
Solution Approach 1:
The system performs preliminary encryption actions on data before it leaves the storage system. Data is encrypted at the source according to its sensitivity labels before being transmitted across networks to distributed processing locations. This preliminary security measure ensures that data remains protected during transmission and processing, mitigating network security risks while enabling distributed processing productivity.
Solution Approach 2:
The encryption parameters are dynamically adjusted based on data sensitivity requirements. Highly sensitive data receives stronger encryption parameters before network transmission, while less sensitive data uses lighter encryption. This parameter adaptation allows the system to maintain strong security for critical data during network transmission while minimizing overhead for less sensitive data, thereby supporting distributed processing efficiency.
Data Source
AI summary
In a computer system with multiple physical computers at different physical locations, a transformer module receives an original query from a client-side computer, analyzes the query statements and annotates the query. The transformer module forwards the annotated query to server-computers. This approach allows a data-analyst 190-ALPHA to use a query that is relatively simple, wherein a data-analyst 190-BETA who does not benefit from the transformer module would have to write a more complex query.