Encrypted Data Search with Segmented Tables and Position Vectors
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Solution Overview
Problem
Searching encrypted data using homomorphic encryption methods results in a significant calculation burden due to the need for binary searches on lookup tables, which is inefficient and resource-intensive.
Innovation Solution
An electronic device that segments and reduces lookup tables using a position identification vector, performing comparison calculations to efficiently locate encrypted data by converting and updating the vector based on search information and table parts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If binary search is performed on a lookup table containing homomorphically encrypted data, then the encrypted data can be searched without decryption, but the calculation burden becomes significant
Solution Approach 1:
The lookup table is divided into multiple segments, and the search process is divided into multiple stages. Each stage processes a segment of the table, reducing the number of elements that need to be processed in each homomorphic comparison operation. This segmentation allows the search to proceed in steps rather than requiring a single complex operation across the entire table.
Solution Approach 2:
The patent introduces a position identification vector as an auxiliary data structure that tracks the search state across different dimensions. Instead of directly comparing search values with all table elements, the vector maintains positional information that guides the search through the segmented table, adding a dimensional layer to the search process that reduces computational complexity.
2Measurement precision
If the lookup table is searched using traditional methods, then all encrypted elements must be processed, but this increases the number of operations required
Solution Approach 1:
The lookup table is divided into multiple segments, and the search process is divided into multiple stages. Each stage processes a segment of the table, reducing the number of elements that need to be processed in each homomorphic comparison operation. This segmentation allows the search to proceed in steps rather than requiring a single complex operation across the entire table.
Solution Approach 2:
The position identification vector is pre-initialized to track potential match positions before the actual comparison operations are performed. This preliminary setup allows the search algorithm to efficiently navigate through the segmented table, avoiding unnecessary comparisons and directly targeting relevant segments based on the vector's state.
Data Source
AI summary
Disclosed is an electronic device including: a memory storing a lookup table including identification information and data matched to the identification information; an interface; and a processor configured to search the data matched to the identification information corresponding to search information by generating a position identification vector including the number of elements corresponding to the number of the lookup table, and repeatedly performing an operation of updating the position identification vector based on a comparison calculation result based on the search information and each segmented table part while segmenting the lookup table into a plurality of parts, in case of receiving the search information through the interface. Accordingly, the device may perform effective data search on the table including a homomorphically encrypted message.