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Multi-key Private Matching for Compute.

Prasad Buddhavarapu, Benjamin M. Case, Logan Gore, Andrew Knox, Payman Mohassel, Shubho Sengupta, Erik Taubeneck, Min Xue

Published Jan 1, 2021• 2 citations
OpenAlex

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We develop a new multi-party generalization of Naor-Nissim indirect indexing, making it possible for many participants to simulate a RAM machine with only poly-logarithmic blow-up. Underlying our approach is a new multi-party variant of oblivious transfer which may be of independent interest. Our most efficient instantiation (built from length-flexible additively homomorphic public key encryption) improves the communication complexity of secure multi-party computation for a number of problems in the literature. We explore, in depth, some of these applications, including private distributed constraint satisfaction problems, private stable bipartite matching, and private longest common subsequence. In the case of the private bipartite stable matching (stable marriage) problem, we follow-up the work of Golle (Financial Crypto 2006) who motivates the application and introduces a novel framework for the solving the problem. We show that the communication complexity of Golle’s main protocol is substantially greater than what was claimed, in part due to surprising pathological behavior of Golle’s variant of the Gale-Shapley stable matching algorithm. We develop new secure protocols in Golle’s basic framework with greatly reduced communication complexity. In the case of the longest common subsequence problem, we design communication efficient two-party and multi-party protocols for several variants of this and related problems. Our protocols achieve the first improvement to the communication complexity for this application over generic results (such as Yao’s garbled circuit protocol). As such, this result is interesting as a contribution to the theory of communication efficiency for secure two-party and multi-party applications. We benefit from the felicitous interplay of an efficient block-retrieval PIR (Gentry-Ramzan, ICALP 2005) with the classic “four Russians” algorithmic design. We believe this technique will be useful for privately implementing a variety of “efficiently encodable” dynamic programming applications.
In this study, we propose a novel post‐quantum private set intersection (PSI) protocol based on the ring learning with errors (RLWE) assumption. Different from existing PSI protocols based on post‐quantum oblivious pseudorandom functions (EUROCRYPT’25) and fully homomorphic encryption (FHE) (CCS’21), our construction follows the Diffie–Hellman (DH)‐based PSI paradigm and uses post‐quantum key exchange to achieve PSI functionality. Our key technique is a signal matching (SigMa) mechanism, which determines whether two items match by checking the consistency of the reconciliation signals derived from their corresponding shared keys. The resulting PSI protocol completes in three rounds. In the first two rounds, the parties exchange RLWE‐based public keys associated with their items; in the third round, the sender transmits the corresponding signals. The receiver then applies SigMa to compare the received signals with its locally computed signals and thereby identify the intersection. We implement our protocol and compare it with Cong et al. (CCS’21) and Heimberger et al. (EUROCRYPT’25). Our protocol achieves the lowest online communication across all evaluated symmetric and asymmetric set‐size configurations, at the cost of additional offline communication. It also achieves the lowest online and total times among the evaluated protocols for all symmetric settings with | X | = | Y | ∈ {2 12 , 2 16 , 2 20 } and all asymmetric settings with | X | ∈ {2 12 , 2 16 , 2 20 } and | Y | ∈ {5535, 11041}. We believe that our work not only supplements existing post‐quantum PSI frameworks but also opens the opportunity for broader applications of post‐quantum PSI.
In secure multi-party computations (SMC), parties wish to compute a function on their private data without revealing more information about their data than what the function reveals. In this paper, we investigate two Shannon-type questions on this problem. We first consider the traditional one-shot model for SMC which does not assume a probabilistic prior on the data. In this model, private communication and randomness are the key enablers to secure computing, and we investigate a notion of randomness cost and capacity. We then move to a probabilistic model for the data, and propose a Shannon model for discrete memoryless SMC. In this model, correlations among data are the key enablers for secure computing, and we investigate a notion of dependency which permits the secure computation of a function. While the models and questions are general, this paper focuses on summation functions and relies on polar code constructions.