Private Set Intersection via Anonymous Third-Party Mediation
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Solution Overview
Problem
Existing PSI protocols fail to enable parties to determine set intersections without revealing the identity of matching parties, are computationally inefficient for large numbers of parties, and do not maintain device anonymity.
Innovation Solution
A system utilizing a transformation engine and an evaluation engine, where the transformation engine applies a pseudorandom function to each party's set without accessing the key, and the evaluation engine checks for set intersections using transformed values, ensuring anonymity and reducing computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional PSI protocols are used to determine set intersections, then the intersection can be found, but the identity of matching parties is revealed and device anonymity is lost
Solution Approach 1:
The patent introduces a third-party service provider as an intermediary to perform the PSI computation. The service provider receives transformed data from multiple computing devices, computes the intersection, and returns results without learning which devices share common data elements. This mediator approach enables intersection finding while preserving device anonymity, as the service provider never identifies which specific devices have matching data.
Solution Approach 2:
The patent applies transformations (such as salting or hashing) to create transformed copies of the data elements before comparison. These transformed versions allow the system to compare data without exposing the original data or identifying which original data elements match, thereby maintaining anonymity while enabling intersection detection.
2Adaptability or versatility
If PSI protocols process large numbers of parties, then more comprehensive intersection detection is achieved, but computational efficiency deteriorates
Solution Approach 1:
The patent divides the PSI computation into separate stages: data transformation at individual computing devices and intersection computation at a centralized service provider. This segmentation allows each device to independently prepare transformed data without performing expensive comparison operations, while the service provider efficiently processes intersections across all parties using the pre-transformed data.
Solution Approach 2:
The third-party service provider acts as a mediator that handles the computationally intensive intersection calculation across all parties. By centralizing this function, the system achieves efficient processing of large numbers of parties without requiring each individual device to perform costly comparison operations, thus improving overall computational efficiency.
Data Source
AI summary
A method for detecting a private set intersection includes receiving, at a third computing device, a first plurality of transformed data elements from a first computing device; receiving, at the third computing device, a second plurality of transformed data elements from a second computing device, wherein an identity of the first computing device is unknown to the second computing device and an identity of the second computing device is unknown to the first computing device; and transmitting, by a processing device executing on the third computing device to the first computing device and the second computing device, an indication of a subset of transformed data elements that are present in both the first plurality of transformed data elements and the second plurality of transformed data elements.