Secure computation enables mutually distrusting parties to jointly evaluate a function on their private inputs without revealing anything but the function's output. Generic secure computation protocols in the semi-honest model have been studied extensively and several best practices have evolved. In this work, we design and implement a mixed-protocol framework, called ABY, that efficiently combines secure computation schemes based on Arithmetic sharing, Boolean sharing, and Yao's garbled circuits and that makes available best practice solutions in secure two-party computation. Our framework allows to pre-compute almost all cryptographic operations and provides novel, highly efficient conversions between secure computation schemes based on pre-computed oblivious transfer extensions. ABY supports several standard operations and we perform benchmarks on a local network and in a public intercontinental cloud. From our benchmarks we deduce new insights on the efficient design of secure computation protocols, most prominently that oblivious transfer-based multiplications are much more efficient than multiplications based on homomorphic encryption. We use ABY to construct mixed-protocols for three example applications-private set intersection, biometric matching, and modular exponentiation-and show that they are more efficient than using a single protocol. Keywords-secure two-party computation; mixed-protocols; efficient protocol design Permission to freely reproduce all or part of this paper for noncommercial purposes is granted provided that copies bear this notice and the full citation on the first page. Reproduction for commercial purposes is strictly prohibited without the prior written consent of the Internet Society, the first-named author (for reproduction of an entire paper only), and the author's employer if the paper was prepared within the scope of employment.

Abstract. Protocols for secure computation enable parties to compute a joint function on their private inputs without revealing anything but the result. A foundation for secure computation is oblivious transfer (OT), which traditionally requires expensive public key cryptography. A more efficient way to perform many OTs is to extend a small number of base OTs using OT extensions based on symmetric cryptography. In this work we present optimizations and efficient implementations of OT and OT extensions in the semi-honest model. We propose a novel OT protocol with security in the standard model and improve OT extensions with respect to communication complexity, computation complexity, and scalability. We also provide specific optimizations of OT extensions that are tailored to the secure computation protocols of Yao and GoldreichMicali-Wigderson and reduce the communication complexity even further. We experimentally verify the efficiency gains of our protocols and optimizations. By applying our implementation to current secure computation frameworks, we can securely compute a Levenshtein distance circuit with 1.29 billion AND gates at a rate of 1.2 million AND gates per second. Moreover, we demonstrate the importance of correctly implementing OT within secure computation protocols by presenting an attack on the FastGC framework.

Private set intersection (PSI) allows two parties to compute the intersection of their sets without revealing any information about items that are not in the intersection. It is one of the best studied applications of secure computation and many PSI protocols have been proposed. However, the variety of existing PSI protocols makes it difficult to identify the solution that performs best in a respective scenario, especially since they were not compared in the same setting. In addition, existing PSI protocols are several orders of magnitude slower than an insecure naïve hashing solution, which is used in practice. In this article, we review the progress made on PSI protocols and give an overview of existing protocols in various security models. We then focus on PSI protocols that are secure against semi-honest adversaries and take advantage of the most recent efficiency improvements in Oblivious Transfer (OT) extension, propose significant optimizations to previous PSI protocols, and suggest a new PSI protocol whose runtime is superior to that of existing protocols. We compare the performance of the protocols, both theoretically and experimentally, by implementing all protocols on the same platform, give recommendations on which protocol to use in a particular setting, and evaluate the progress on PSI protocols by comparing them to the currently employed insecure naïve hashing protocol. We demonstrate the feasibility of our new PSI protocol by processing two sets with a billion elements each. CCS Concepts: • Security and privacy → Privacy-preserving protocols;

Designing an efficient cipher was always a delicate balance between linear and non-linear operations. This goes back to the design of DES, and in fact all the way back to the seminal work of Shannon. Here we focus, for the first time, on an extreme corner of the design space and initiate a study of symmetric-key primitives that minimize the multiplicative size and depth of their descriptions. This is motivated by recent progress in practical instantiations of secure multi-party computation (MPC), fully homomorphic encryption (FHE), and zero-knowledge proofs (ZK) where linear computations are, compared to non-linear operations, essentially "free". We focus on the case of a block cipher, and propose the family of block ciphers "LowMC", beating all existing proposals with respect to these metrics by far. We sketch several applications for such ciphers and give implementation comparisons suggesting that when encrypting larger amounts of data the new design strategy translates into improvements in computation and communication complexity by up to a factor of 5 compared to AES-128, which incidentally is one of the most competitive classical designs. Furthermore, we identify cases where "free XORs" can no longer be regarded as such but represent a bottleneck, hence refuting this commonly held belief with a practical example.

Secure two-party computation is a rapidly emerging field of research and enables a large variety of privacy-preserving applications such as mobile social networks or biometric identification. In the late eighties, two different approaches were proposed: Yao's garbled circuits and the protocol of Goldreich-Micali-Wigderson (GMW). Since then, research has mostly focused on Yao's garbled circuits as they were believed to yield better efficiency due to their constant round complexity. In this work we give several optimizations for an efficient implementation of the GMW protocol. We show that for semi-honest adversaries the optimized GMW protocol can outperform today's most efficient implementations of Yao's garbled circuits, but highly depends on a low network latency. As a first step to overcome these latency issues, we summarize depth-optimized circuit constructions for various standard tasks. As application scenario we consider privacy-preserving face recognition and show that our optimized framework is up to 100 times faster than previous works even in settings with high network latency.