Encrypted Range Queries Using Hypergraph Equality Mapping
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Solution Overview
Problem
Existing database systems face challenges in efficiently executing range queries on encrypted data due to high storage overhead and security vulnerabilities, particularly in compaction protocols that leak distance information.
Innovation Solution
A database system utilizing a range hypergraph and compaction protocol that transforms range queries into equality queries, employing a skip-level hypergraph with sparsity and trimming factors to reduce node competition and insert dummy values, ensuring high-throughput and reduced leakage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a range query is executed on encrypted data using conventional compaction protocols, then query processing is enabled, but distance information leakage occurs
Solution Approach 1:
The patent introduces a range hypergraph as an intermediary structure between the encrypted data and the range query. This hypergraph maps range queries to multiple equality queries through intermediate nodes, allowing the system to process range queries on encrypted data without directly comparing encrypted values, thus preventing distance information leakage while enabling query processing
Solution Approach 2:
The patent segments the range query into multiple equality queries by decomposing the range into sub-ranges represented by hypergraph nodes. Each equality query operates on a subset of the range, and the results are aggregated to produce the final range query result. This segmentation prevents direct exposure of distance information while maintaining query functionality
2Adaptability or versatility
If a range hypergraph with many nodes is used to represent all possible range queries, then query coverage is complete, but storage overhead increases
Solution Approach 1:
The patent applies local quality by selectively including only the necessary nodes in the range hypergraph based on the actual data distribution and query patterns. Instead of pre-creating all possible nodes, the system dynamically determines which nodes are needed for a given dataset and query workload, reducing storage overhead while maintaining complete range query coverage
Solution Approach 2:
The patent makes the rangehypergraph dynamic by allowing it to be adapted to different datasets and query patterns. The hypergraph structure can be modified and reconfigured based on the actual data characteristics, enabling the system to maintain versatility while minimizing storage requirements through dynamic adjustment rather than static pre-definition
3Quantity of substance
If standard compaction protocols are used to reduce storage, then storage overhead decreases, but security vulnerabilities increase due to distance information leakage
Solution Approach 1:
The patent converts the potentially harmful effect of compaction (which can leak distance information) into a beneficial process by designing a specialized compaction protocol that operates on the range hypergraph. This protocol maintains the storage reduction benefits of compaction while preventing distance information leakage through the intermediary hypergraph structure that maps queries without exposing underlying encrypted value relationships
Data Source
AI summary
Described herein are database systems that execute range queries on encrypted data. Provided is a numerical encoding scheme provides a set of order-preserving functions that maps all numerical data types supported by the database systems to a compact set of positive integers representative of the range query. Stored encrypted data may also be represented as positive integers. The positive integers from the range query may then be used to execute a set of equality queries on the stored encrypted data. Also provided is a range hypergraph supporting range queries to be executed on the encrypted data with high-throughput and without high amounts of storage overhead. Additionally, a hypergraph-friendly compaction protocol may be performed with padded inputs, in order to reduce leakage for range queries.