Private Set Intersection with Hidden Match Count
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Solution Overview
Problem
Existing private set intersection schemes expose the size of the intersection set, allowing malicious participants to indirectly obtain data through member reasoning, compromising data security.
Innovation Solution
A data processing method involving shuffling, ID randomization, and homomorphic encryption to construct confusion elements and apply secret sharing, ensuring the size of the intersection set remains confidential.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If existing private set intersection schemes are used to obtain calculation or analysis results, then the intersection set size can be obtained, but data security is compromised as malicious participants can indirectly obtain data through member reasoning
Solution Approach 1:
The patent segments the private set intersection protocol into multiple independent modules: homomorphic encryption module for encrypting data, secret sharing module for splitting intersection results, and confusion element generation module for adding dummy elements. Each module performs a specific function, collectively achieving secure intersection computation while preventing information leakage about the true intersection size
Solution Approach 2:
The patent introduces homomorphic encryption as an intermediary mechanism that allows computation on encrypted data without decryption. This intermediary layer enables the protocol to compute intersection results while keeping the data encrypted throughout the process, preventing malicious participants from inferring the true intersection size from intermediate results
2Productivity
If the size of the private intersection is exposed to participants, then intersection calculation can be completed, but malicious participants can indirectly obtain data from the data sets
Solution Approach 1:
The patent applies preliminary anti-action by pre-generating confusion elements (dummy elements) and preparing secret sharing schemes before the actual intersection computation. These pre-prepared components are designed to counteract potential information leakage, ensuring that even if participants attempt to infer the true intersection size, they will instead receive the size of the confused intersection set that includes dummy elements
Solution Approach 2:
The patent changes the parameter being measured from the true intersection size to the confused intersection size that includes dummy elements. By transforming the output parameter from |A ∩ B| to |A ∩ B ∪ C| where C is the set of confusion elements, the protocol maintains calculation efficiency while altering the observable parameter to prevent data inference
Data Source
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AI summary
A data processing method, an apparatus, a device and a medium are provided. The method includes: receiving a first set obtained by a second participant shuffling and ID-randomizing its set and replacing features with first-homomorphic-ciphertexts; obtaining a second set by shuffling and ID-randomizing a collection set of the a first participant's set and imitation elements, and replacing features of collection set elements with second-homomorphic-ciphertexts and sending the second set to the second-participant; receiving a third set obtained by the second-participant splitting second homomorphic ciphertexts into second-shared-ciphertexts and second-shared-numbers and replacing the second-homomorphic-ciphertexts with the second-shared-ciphertexts; splitting the first-homomorphic-ciphertexts of intersection elements and confusion elements of third and fourth sets into first-shared-ciphertexts and first-shared-numbers; splitting a first/second preset value to obtain IDs of the intersection /confusion elements; constructing a first-feature-union-set according to the second-shared-ciphertexts, the first-shared-numbers and the IDs; and sending the first-shared-ciphertexts and the IDs to the second participant.