Homomorphic Database Operations for Secure Transaction Querying
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Solution Overview
Problem
Current database systems lack efficient methods for securely storing and querying transaction data while maintaining data privacy, especially when comparing performance metrics across competitors without exposing underlying data.
Innovation Solution
The Homomorphic Database Operations (HEDO) system employs homomorphic encryption to enable secure storage and querying of transaction data, allowing merchants to compare performance metrics without accessing competitors' underlying data, using homomorphic cross-table joins and encrypted models to maintain semantic security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional database systems store transaction data in plaintext for efficient querying, then query speed and operational efficiency are improved, but data privacy and security are compromised
Solution Approach 1:
The patent transforms the state of data from plaintext to homomorphically encrypted ciphertext, changing the parameter of data representation. This allows the database to maintain operational efficiency while securing data privacy, as homomorphic encryption enables computations on encrypted data without decryption
Solution Approach 2:
The patent introduces homomorphic encryption as an intermediary layer between the stored data and the processing operations. This intermediary enables secure data storage and querying by allowing the database system to operate on encrypted data through specialized homomorphic operations, preventing direct data exposure while maintaining functionality
2Measurement precision
If merchants access competitors' underlying transaction data for performance comparison, then competitive analysis accuracy is improved, but data security and privacy protection are worsened
Solution Approach 1:
The patent creates encrypted copies of transaction data that preserve the structural and statistical properties needed for competitive analysis while preventing access to actual data values. Merchants can compare performance metrics using these encrypted representations without exposing sensitive underlying information
Solution Approach 2:
The patent changes the parameter of data representation to homomorphically encrypted form, which maintains the mathematical properties necessary for accurate performance comparison while eliminating direct data exposure. This allows precise competitive analysis through encrypted metric comparison
3Reliability
If transaction data is encrypted using traditional encryption methods, then data security is improved, but querying and aggregation operations become computationally infeasible
Solution Approach 1:
The patent changes the type of encryption from traditional symmetric or asymmetric encryption to homomorphic encryption, which has the special property of allowing computations on encrypted data. This parameter change enables both data security and operational feasibility by permitting aggregation and querying operations directly on ciphertext
Solution Approach 2:
The patent replaces traditional decryption-then-compute mechanics with homomorphic computation mechanics. Instead of decrypting data and then performing operations, the system performs homomorphic operations directly on encrypted data, substituting the mechanical process to maintain both security and functionality
Data Source
AI summary
An encrypted table value homomorphically joining method and apparatus comprising receiving a query input. Based on the query input, the method may include determining at least one field on which to join the plurality of tables, and determining that the at least one field contains deterministically homomorphically encrypted data. The method may include determining a homomorphic join strategy directly comparing values in two homomorphically encrypted fields, performing a homomorphic join on the fields in the plurality of tables, and providing resultant homomorphically joined tables.