Hierarchical Data Spaces for Encrypted Constant-Time Data Access
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Relational and non-relational data management systems face inefficiencies in data operations due to the need to scan entire columns of unsorted values, exposing data when stored or transmitted, and lack of effective encryption methods to protect data integrity.
Innovation Solution
A system utilizing hierarchical data spaces (LHDS) that subdivides data into logical spaces with hierarchical path identifiers (HPId) for probabilistic operations, allowing encrypted storage and transmission while preserving data hierarchy, enabling efficient access and reduced inference risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If relational data management systems store data in column-oriented approaches with unsorted values, then data can be stored flexibly, but the system must scan the entire column of values to perform operations, resulting in low efficiency
Solution Approach 1:
The patent segments the data space into hierarchical subdivisions (HDS) that organize data values into structured regions. Instead of scanning entire unsorted columns, the system divides the data space into manageable segments that can be efficiently searched and accessed, transforming the linear scan problem into a hierarchical navigation problem.
Solution Approach 2:
The patent introduces a hierarchical dimension to the traditional flat columnar storage model. By organizing data in hierarchical subdivisions with multiple levels (root subdivision, child subdivisions, etc.), the system adds a vertical dimension to data access, enabling efficient navigation through hierarchical path identifiers rather than linear scanning.
2Reliability
If data is stored or transmitted in traditional systems, then data can be accessed and processed, but data is exposed and vulnerable to security risks
Solution Approach 1:
The patent introduces hierarchical path identifiers (HPId) as intermediaries between the data storage structure and the query system. HPIds serve as encrypted mediators that enable efficient data location and access without exposing the actual data values, allowing secure operations through probabilistic matching of path identifiers rather than direct data inspection.
Solution Approach 2:
The patent creates and operates on copies of hierarchical path identifiers rather than the actual data values. By performing operations on HPId copies and only accessing decrypted data when necessary, the system maintains security while enabling efficient processing, as the path identifiers can be manipulated without exposing sensitive information.
3Reliability
If traditional encryption methods are used to protect data, then data security is improved, but data operations require decryption which reduces efficiency
Solution Approach 1:
The patent extracts the security-critical information from the actual data values and places it into the hierarchical path identifier structure. By moving the essential routing and identification information into HPIds that can be encrypted and operated upon independently, the system separates security functions from data processing functions, allowing encrypted operations without full decryption.
Solution Approach 2:
The patent changes the parameter being operated on from raw data values to hierarchical path identifiers. This parameter transformation allows the system to perform efficient probabilistic operations on encrypted HPIds rather than requiring decryption of the actual data values, maintaining both security and operational efficiency.
4Productivity
If entire columns of data are scanned for operations, then all data can be processed, but the complexity of data operations increases
Solution Approach 1:
The patent performs preliminary organization of data into hierarchical subdivisions and pre-computation of hierarchical path identifiers during data insertion. This preliminary structuring enables subsequent operations to navigate efficiently through the pre-organized hierarchy rather than scanning and processing entire columns, reducing operational complexity while maintaining completeness.
Data Source
AI summary
A method for storing or transmitting information may include determining at least one subdivision of at least one logical hierarchical data space. The at least one logical hierarchical data space may have a plurality of subdivisions. The method may further include creating at least one data block. The method may further include writing the at least one tuple to the at least one data block. The at least one tuple may be associated with the subdivision of the at least one logical hierarchical data space. The method may further include associating the at least one data block with the at least one subdivision of the at least one logical hierarchical data space.