MK
M. Kozik
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A Bridge Between Private Set Intersection Algorithms
Transforming MPSI into OT-MPSI
Financial criminals often manage to avoid being detected. Although banks can nowadays easily query and analyse the financial data they have access to, it is still an issue when multiple banks need to collaborate with each other to catch a criminal. Privacy laws prohibit them from simply sharing all their data with each other. Hence, methods for privately sharing their data are needed to ensure a smooth and secure collaboration. Computing a function between multiple parties, while keeping their inputs secure, is called a Secure Multiparty Computation (SMPC). One of its subtypes is Multiparty Private Set Intersection (MPSI). It allows for computing an intersection between multiple sets without revealing them. A special case of MPSI is Threshold-MPSI (T-MPSI), which returns items that are in at least T sets, while still keeping the actual sets hidden. Although these two protocols are closely correlated, there is no secure or efficient protocol to transform one into the other. Therefore, we focus our paper on making a step towards finding one. We design a transformation from MPSI to a slightly weaker variant of T-MPSI, which still keeps the information of who contributed an item to the intersection secure by utilising dummy Bloom Filters and Mental Poker. We focus our paper on the security aspect of the protocol, while keeping the efficiency bottleneck of the current state-of-the-art solution. Therefore, the experimental results of the runtime indicate that it is not yet a practical solution. However, it marks a step towards finding one.
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Financial criminals often manage to avoid being detected. Although banks can nowadays easily query and analyse the financial data they have access to, it is still an issue when multiple banks need to collaborate with each other to catch a criminal. Privacy laws prohibit them from simply sharing all their data with each other. Hence, methods for privately sharing their data are needed to ensure a smooth and secure collaboration. Computing a function between multiple parties, while keeping their inputs secure, is called a Secure Multiparty Computation (SMPC). One of its subtypes is Multiparty Private Set Intersection (MPSI). It allows for computing an intersection between multiple sets without revealing them. A special case of MPSI is Threshold-MPSI (T-MPSI), which returns items that are in at least T sets, while still keeping the actual sets hidden. Although these two protocols are closely correlated, there is no secure or efficient protocol to transform one into the other. Therefore, we focus our paper on making a step towards finding one. We design a transformation from MPSI to a slightly weaker variant of T-MPSI, which still keeps the information of who contributed an item to the intersection secure by utilising dummy Bloom Filters and Mental Poker. We focus our paper on the security aspect of the protocol, while keeping the efficiency bottleneck of the current state-of-the-art solution. Therefore, the experimental results of the runtime indicate that it is not yet a practical solution. However, it marks a step towards finding one.