Encrypted Table Query Partitioning Against Frequency Analysis
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Solution Overview
Problem
Existing data table query methods using deterministic encryption are vulnerable to frequency analysis attacks, leading to potential leaks of plaintext data due to the exposure of encrypted data frequency statistics.
Innovation Solution
The method involves converting a data table query request into multiple sub-table query requests, randomly transmitting these requests to a server, and generating query results that obscure statistical analysis, thereby obfuscating the frequency of encrypted data appearance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If deterministic encryption algorithm is used to encrypt data in data table, then data security is improved, but frequency analysis attack vulnerability increases
Solution Approach 1:
The patent divides the data table into multiple data sub-tables based on attribute values, and sends multiple query requests to query these sub-tables. This segmentation approach prevents frequency analysis attacks by distributing data across multiple tables, making it difficult for attackers to analyze frequency patterns of encrypted data.
Solution Approach 2:
The patent introduces a random number generator as an intermediary to generate random numbers for obfuscating query request transmission sequences and query result transmission sequences. This intermediary mechanism prevents attackers from predicting the order of data transmission, thereby mitigating frequency analysis attacks while maintaining data security.
2Productivity
If hash-join method is used to query data in multiple data tables, then query efficiency is improved, but frequency information leakage increases
Solution Approach 1:
The patent segments the data tables into multiple sub-tables and queries them separately using multiple query requests. This segmentation prevents frequency information leakage while maintaining query efficiency by processing data in smaller, manageable units rather than joining entire tables.
Solution Approach 2:
The patent creates multiple copies of query requests with different transmission sequences and sends them to query the data sub-tables. These copies include random obfuscation that prevents frequency analysis while ensuring all necessary data is retrieved for accurate query results.
3Reliability
If multiple query requests are sent to query data sub-tables, then query completeness is improved, but transmission sequence predictability increases
Solution Approach 1:
The patent dynamically generates random numbers for each query request transmission sequence using a random number generator. This dynamic approach ensures that the transmission sequence is unpredictable and changes with each query operation, preventing frequency analysis attacks while maintaining query completeness.
Solution Approach 2:
The patent uses a random number generator as an intermediary to introduce randomness into the query request transmission sequences. This intermediary mechanism ensures that even though multiple queries are sent, their sequences remain unpredictable and cannot be used for frequency analysis.
Data Source
AI summary
This application discloses a method for querying a data table. The method includes acquiring a data table query request to query a second data table on a server for attribute values of a second attribute matching attribute values of a first attribute in a first data table on the server; converting the data table query request into a first group of data sub-table query requests requesting to query a second group of data sub-tables for attribute values of the second attribute matching attribute values of the first attribute in a first group of data sub-tables; generating a second group of data sub-table query requests; and transmitting the first group of data sub-table query requests and the second group of data sub-table query requests to the server, and acquiring a first group of query results and a second group of query results from the server.