A multi-party private join (MPPJ) protocol enables multiple source parties to provide a receiver party with the inner joins over their respective datasets, while revealing as little information as possible. There is currently no protocol that directly and efficiently enables such a MPPJ beyond the two- or three-party setting. The presently known protocols either achieve weaker functionality (e.g., multi- party private set intersection protocols) or more general ones (e.g., private-join-compute and generic secure multi-party computation protocols) and are therefore more costly to run for the sources. This work formally introduces MPPJ as an explicit goal, and proposes an efficient, helper-assisted protocol that achieves 𝑛-party inner joins with small leakage and close-to-optimal overhead for the sources. Specifically, for 𝑛 databases with 𝑚 rows, it requires only a single 𝑂 (𝑚) upload from the sources to the helper, and a single 𝑂 (𝑛 · 𝑚) download from the helper to the receiver. Moreover, the helper is entirely oblivious: it enables the efficiency and simplicity goals we are striving for, but it does not learn anything about the computation it facilitates. We formally model and prove the security of our protocol from standard assumptions, in the passive-adversary model. Then, we provide an open-source implementation and an extensive performance evaluation. According to our experiments, our protocol requires 1.02 to 20 times less communication than a current private-join-compute protocol (with no computation over the join) for 2 to 6 parties and input database sizes from 1.5K to 250K records. Finally, we demonstrate the versatility of our approach by extending our protocol to threshold-joins.

We revisit the problem of constructing protocols for multiparty private set intersection (MPSI) in light of the recent advances in multiparty homomorphic encryption (MHE). In MPSI, N ≥ 2 parties jointly compute the intersection of their respective private set. Kissner and Song proposed an MHE-based MPSI scheme in 2005, but their approach was limited by the then-available HE schemes. Today, however, MHE schemes have become both more versatile and more efficient. As an early result, we implemented the MPSI approach of Kissner et al. with the recently proposed Helium framework (CCS 2024) for MHE-based MPC. We show that even this simple protocol can outperform the state-of-the-art implementation (in the passive-adversary setting) by Kolesnikov et al. (CCS 2017), both in terms of latency and communication cost.

Multiparty fully homomorphic encryption (MFHE) schemes enable multiple parties to efficiently compute functions on their sensitive data while retaining confidentiality. However, existing MFHE schemes guarantee data confidentiality and the correctness of the computation result only against honest-but-curious adversaries. In this work, we provide the first practical construction that enables the verification of MFHE operations in zero-knowledge, protecting MFHE from malicious adversaries. Our solution relies on a combination of lattice-based commitment schemes and proof systems which we adapt to support both modern FHE schemes and their implementation optimizations. We implement our construction in PELTA. Our experimental evaluation shows that PELTA is one to two orders of magnitude faster than existing techniques in the literature.

Abstract We propose and implement a multiparty homomorphic encryption (MHE) scheme with a $$t$$ t -out-of- $$N$$ N -threshold access-structure that is efficient and does not require a trusted dealer in the common random string model. We construct this scheme from the ring-learning-with-error assumptions and as an extension of the MHE scheme of Mouchet et al. (PETS 21). By means of a specially adapted share re-sharing procedure, this extension can be used to relax the $$N$$ N -out-of- $$N$$ N -threshold access-structure of the original scheme into a $$t$$ t -out-of- $$N$$ N -threshold one. This procedure introduces only a single round of communication during the setup phase, after which any set of at least t parties can compute a t -out-of- t additive sharing of the secret-key with no interaction; this new sharing can be used directly in the scheme of Mouchet et al. We show that, by performing Shamir re-sharing over the MHE ciphertext-space ring with a carefully chosen exceptional set, this reconstruction procedure can be made secure and has negligible overhead. Moreover, it only requires the parties to store a constant-size state after its setup phase. Hence, in addition to fault tolerance, lowering the corruption threshold also yields considerable efficiency benefits, by enabling the distribution of batched secret-key operations among the online parties. We implemented and open-sourced our scheme in the Lattigo library.

Abstract We propose and evaluate a secure-multiparty-computation (MPC) solution in the semi-honest model with dishonest majority that is based on multiparty homomorphic encryption (MHE). To support our solution, we introduce a multiparty version of the Brakerski-Fan-Vercauteren homomorphic cryptosystem and implement it in an open-source library. MHE-based MPC solutions have several advantages: Their transcript is public, their o~ine phase is compact, and their circuit-evaluation procedure is noninteractive. By exploiting these properties, the communication complexity of MPC tasks is reduced from quadratic to linear in the number of parties, thus enabling secure computation among potentially thousands of parties and in a broad variety of computing paradigms, from the traditional peer-to-peer setting to cloud-outsourcing and smart-contract technologies. MHE-based approaches can also outperform the state-of-the-art solutions, even for a small number of parties. We demonstrate this for three circuits: private input selection with application to private-information retrieval, component-wise vector multiplication with application to private-set intersection, and Beaver multiplication triples generation. For the first circuit, privately selecting one input among eight thousand parties’ (of 32 KB each) requires only 1.31 MB of communication per party and completes in 61.7 seconds. For the second circuit with eight parties, our approach is 8.6 times faster and requires 39.3 times less communication than the current methods. For the third circuit and ten parties, our approach generates 20 times more triples per second while requiring 136 times less communication per-triple than an approach based on oblivious transfer. We implemented our scheme in the Lattigo library and open-sourced the code at github.com/ldsec/lattigo.

Abstract Current solutions for privacy-preserving data sharing among multiple parties either depend on a centralized authority that must be trusted and provides only weakest-link security (e.g., the entity that manages private/secret cryptographic keys), or leverage on decentralized but impractical approaches (e.g., secure multi-party computation). When the data to be shared are of a sensitive nature and the number of data providers is high, these solutions are not appropriate. Therefore, we present UnLynx, a new decentralized system for efficient privacy-preserving data sharing. We considermservers that constitute a collective authority whose goal is to verifiably compute on data sent fromndata providers. UnLynxguarantees the confidentiality, unlinkability between data providers and their data, privacy of the end result and the correctness of computations by the servers. Furthermore, to support differentially private queries, UnLynxcan collectively add noise under encryption. All of this is achieved through a combination of a set of new distributed and secure protocols that are based on homomorphic cryptography, verifiable shuffling and zero-knowledge proofs. UnLynxis highly parallelizable and modular by design as it enables multiple security/privacy vs. runtime tradeoffs. Our evaluation shows that UnLynxcan execute a secure survey on 400,000 personal data records containing 5 encrypted attributes, distributed over 20 independent databases, for a total of 2,000,000 ciphertexts, in 24 minutes.