Secure multi-party computation

About: Secure multi-party computation is a research topic. Over the lifetime, 4827 publications have been published within this topic receiving 124027 citations.

Faster secure two-party computation using garbled circuits

Abstract: Secure two-party computation enables two parties to evaluate a function cooperatively without revealing to either party anything beyond the function’s output. The garbled-circuit technique, a generic approach to secure two-party computation for semi-honest participants, was developed by Yao in the 1980s, but has been viewed as being of limited practical significance due to its inefficiency. We demonstrate several techniques for improving the running time and memory requirements of the garbled-circuit technique, resulting in an implementation of generic secure two-party computation that is significantly faster than any previously reported while also scaling to arbitrarily large circuits. We validate our approach by demonstrating secure computation of circuits with over 10 9 gates at a rate of roughly 10 ms per garbled gate, and showing order-of-magnitude improvements over the best previous privacy-preserving protocols for computing Hamming distance, Levenshtein distance, Smith-Waterman genome alignment, and AES.

ABY - A Framework for Efficient Mixed-Protocol Secure Two-Party Computation

Abstract: from details of underlying secure computation protocol Use only fast symmetric key crypto Code is available on GitHub: http://encrypto.de/code/ABY

Secure Multiparty Computation for Privacy-Preserving Data Mining

Abstract: In this paper, we survey the basic paradigms and notions of secure mul- tiparty computation and discuss their relevance to the fleld of privacy-preserving data mining. In addition to reviewing deflnitions and constructions for secure mul- tiparty computation, we discuss the issue of e-ciency and demonstrate the di-cul- ties involved in constructing highly e-cient protocols. We also present common errors that are prevalent in the literature when secure multiparty computation techniques are applied to privacy-preserving data mining. Finally, we discuss the relationship between secure multiparty computation and privacy-preserving data mining, and show which problems it solves and which problems it does not.

Founding Cryptography on Oblivious Transfer --- Efficiently

Abstract: We present a simple and efficient compiler for transforming secure multi-party computation (MPC) protocols that enjoy security only with an honest majority into MPC protocols that guarantee security with no honest majority, in the oblivious-transfer (OT) hybrid model. Our technique works by combining a secure protocol in the honest majority setting with a protocol achieving only security against semi-honestparties in the setting of no honest majority. Applying our compiler to variants of protocols from the literature, we get several applications for secure two-party computation and for MPC with no honest majority. These include: Constant-rate two-party computation in the OT-hybrid model. We obtain a statistically UC-secure two-party protocol in the OT-hybrid model that can evaluate a general circuit Cof size sand depth dwith a total communication complexity of O(s) + poly(k, d, log s) and O(d) rounds. The above result generalizes to a constant number of parties. Extending OTs in the malicious model. We obtain a computationally efficient protocol for generating many string OTs from few string OTs with only a constant amortized communication overheadcompared to the total length of the string OTs. Black-box constructions for constant-round MPC with no honest majority. We obtain general computationally UC-secure MPC protocols in the OT-hybrid model that use only a constant number of rounds, and only make a black-boxaccess to a pseudorandom generator. This gives the first constant-round protocols for three or more parties that only make a black-box use of cryptographic primitives (and avoid expensive zero-knowledge proofs).

Secure Multiparty Computation Goes Live

Abstract: In this note, we report on the first large-scale and practical application of secure multiparty computation, which took place in January 2008. We also report on the novel cryptographic protocols that were used.