Private Set Intersection Using Homomorphic Encryption
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Solution Overview
Problem
Conventional private set intersection techniques are inefficient due to the large amount of ciphertext information exchanged, leading to high communication bandwidth and storage requirements, especially when dealing with data strings exceeding 32 bits.
Innovation Solution
The described techniques use homomorphic encryption to segment data into strings, encrypt them individually or collectively, and use a server to create a ciphertext vector by multiplying with a matrix, allowing entities to determine common data strings without revealing other data strings, thus reducing communication bandwidth and storage needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional private set intersection techniques are used to encrypt and exchange data strings, then data privacy is protected, but communication bandwidth and storage requirements increase significantly
Solution Approach 1:
The patent segments data strings into fixed 32-bit blocks and processes them in batches. Instead of encrypting and exchanging entire large data strings individually, the system divides them into smaller segments that can be handled more efficiently, reducing the overall ciphertext volume while maintaining privacy protection
Solution Approach 2:
The patent changes the encryption approach by using homomorphic encryption properties to perform set intersection operations directly on encrypted data without full decryption. This parameter change in the cryptographic approach reduces the amount of ciphertext that needs to be exchanged and stored compared to conventional encryption methods
2Reliability
If conventional private set intersection techniques encrypt data strings exceeding 32 bits, then data privacy is maintained, but processing efficiency and communication speed deteriorate
Solution Approach 1:
The patent segments data strings exceeding 32 bits into multiple fixed-size blocks and processes them in batches. This segmentation allows the system to handle large data strings efficiently by breaking them down into manageable units that can be processed faster while maintaining the same privacy protection level
Solution Approach 2:
The patent uses batch processing where multiple encrypted data blocks are processed together in a single homomorphic encryption operation. This partial action approach processes groups of data segments simultaneously rather than individually, significantly improving processing efficiency while maintaining complete privacy protection
3Productivity
If conventional private set intersection techniques are used, then entities can find common data elements, but communication bandwidth consumption increases due to large encrypted payloads
Solution Approach 1:
The patent merges multiple encrypted data blocks into batched homomorphic encryption operations. By combining multiple data segments into single cryptographic operations, the system reduces the total number of separate ciphertext transmissions required, thereby reducing communication bandwidth consumption while maintaining the ability to find common elements
Solution Approach 2:
The patent changes the cryptographic parameter approach by using homomorphic encryption schemes that allow set intersection operations to be performed on encrypted data with reduced communication overhead. This parameter change enables the system to maintain full set intersection capability while significantly reducing the bandwidth required for exchanging encrypted payloads
Data Source
AI summary
The disclosure herein relates to private set intersection techniques. The described private set intersection techniques enable entities to determine common data strings in their respective data sets. The private set intersection techniques described herein allow those common data strings to be shareable between the entities, while maintaining the secrecy of other data strings stored in their respective data sets.