We revisit the problem of general-purpose private function evaluation (PFE) wherein a single party P1 holds a circuit C, while each Pi for 1 ≤ i ≤ n holds a private input xi, and the goal is for a subset (or all) of the parties to learn C(x1,..., xn) but nothing else. We put forth a general framework for designing PFE where the task of hiding the circuit and securely evaluating its gates are addressed independently: First, we reduce the task of hiding the circuit topology to oblivious evaluation of a mapping that encodes the topology of the circuit, which we refer to as oblivious extended permutation (OEP) since the mapping is a generalization of the permutation mapping. Second, we design a subprotocol for private evaluation of a single gate (PFE for one gate), which we refer to as private gate evaluation (PGE). Finally, we show how to naturally combine the two components to obtain efficient and secure PFE. We apply our framework to several well-known general-purpose MPC constructions, in each case, obtaining the most efficient PFE construction to date, for the considered setting. Similar to the previous work we only consider semi-honest adversaries in this paper. • In the multiparty case with dishonest majority, we apply our techniques to the seminal GMW protocol [GMW87] and obtain the first general-purpose PFE with linear complexity in the circuit
We revisit the problem of general-purpose private function evaluation (PFE) wherein a single party P1 holds a circuit C, while each Pi for 1 ≤ i ≤ n holds a private input xi, and the goal is for a subset (or all) of the parties to learn C(x1,..., xn) but nothing else. We put forth a general framework for designing PFE where the task of hiding the circuit and securely evaluating its gates are addressed independently: First, we reduce the task of hiding the circuit topology to oblivious evaluation of a mapping that encodes the topology of the circuit, which we refer to as oblivious extended permutation (OEP) since the mapping is a generalization of the permutation mapping. Second, we design a subprotocol for private evaluation of a single gate (PFE for one gate), which we refer to as private gate evaluation (PGE). Finally, we show how to naturally combine the two components to obtain efficient and secure PFE. We apply our framework to several well-known general-purpose MPC constructions, in each case, obtaining the most efficient PFE construction to date, for the considered setting. Similar to the previous work we only consider semi-honest adversaries in this paper. • In the multiparty case with dishonest majority, we apply our techniques to the seminal GMW protocol [GMW87] and obtain the first general-purpose PFE with linear complexity in the circuit
In this thesis, we study the problem of general-purpose private function evaluation (PFE) wherein a single party P1 holds a circuit C, while each Pi for 1<=i<=m holds a private input xi, and the goal is for a subset (or all) of the parties to learn C(x1,…,xm) but nothing else. We pursue the design of PFE with better concrete and/or asymptotic complexity for a variety of settings. We put forth a general framework for designing PFE as the first alternative general approach to universal circuits. In this framework, the task of hiding the circuit topology and securely evaluating its gates are addressed independently through two functionalities we call CTH (Circuit Topology Hiding) and PGE (Private Gate Evaluation). We instantiate our framework using the building blocks of several well-known general MPC constructions, obtaining more efficient PFE than prior work for two-party PFE, multi-party PFE and PFE for arithmetic circuits. Next, we propose the first general framework for designing actively secure PFE, not based on universal circuits. On the theoretical side, our framework yields the first actively secure PFE with linear complexity in the circuit size. On the practical side, we obtain the first actively secure PFE for arithmetic circuits with O(glogg) complexity where g is the circuit size, significantly improving over previous constructions with complexity O(g^5). Despite its inefficiency, we identify various advantages for PFE based on universal circuits. Valiant's construction (STOC 1976) yields universal circuits with the optimal asymptotic complexity, and has been employed in several recent works. But somewhat surprisingly, no implementations of the construction exist. We look back at this construction, and provide a more approachable description. This enables us to provide constant factor improvements and the first implementation. A more accurate comparison made possible through our implementation shows that the improved Valiant's UC performs better than the theoretical estimate, and in fact is almost always smaller than the UC construction of Kolesnikov and Schneider (FC 2008). We also observe, for the first time, that the same construction can be adapted to yield size-optimized universal arithmetic circuits (UAC).
Abstract. We propose the first general framework for designing actively secure private function eval-uation (PFE), not based on universal circuits. Our framework is naturally divided into pre-processing and online stages and can be instantiated using any generic actively secure multiparty computation (MPC) protocol. Our framework helps address the main open questions about efficiency of actively secure PFE. On the theoretical side, our framework yields the first actively secure PFE with linear complexity in the circuit size. On the practical side, we obtain the first actively secure PFE for arithmetic circuits with O(g · log g) complexity where g is the circuit size. The best previous construction (of practical interest) is based on an arithmetic universal circuit and has complexity O(g5). We also introduce the first linear Zero-Knowledge proof of correctness of “extended permutation ” of ciphertexts (a generalization of ZK proof of correct shuffles) which maybe of independent interest.
We consider the problem of private function evaluation (PFE) in the two-party setting. Here, informally, one party holds an input x while the other holds a circuit describing a function f; the goal is for one (or both) of the parties to learn f(x) while revealing nothing more to either party. In contrast to the usual setting of secure computation — where the function being computed is known to both parties — PFE is useful in settings where the function (i.e., algorithm) itself must remain secret, e.g., because it is proprietary or classified. It is known that PFE can be reduced to standard secure computation by having the parties evaluate a universal circuit, and this is the approach taken in most prior work. Using a universal circuit, however, introduces additional overhead and results in a more complex implementation. We show here a completely new technique for PFE that avoids universal circuits, and results in constant-round protocols with communication/computational complexity linear in the size of the circuit computing f. This gives the first constant-round protocol for PFE with linear complexity (without using fully homomorphic encryption), even restricted to semi-honest adversaries. 1
Private function evaluation (PFE) is a special case of secure multi-party computation (MPC), where the function to be computed is known by only one party. PFE is useful in several real-life applications where an algorithm or a function itself needs to remain secret for reasons such as protecting intellectual property or security classification level. In this paper, we focus on improving 2-party PFE based on symmetric cryptographic primitives. In this respect, we look back at the seminal PFE framework presented by Mohassel and Sadeghian at Eurocrypt’13. We show how to adapt and utilize the well-known half gates garbling technique (Zahur et al., Eurocrypt’15) to their constant-round 2-party PFE scheme. Compared to their scheme, our resulting optimization significantly improves the efficiency of both the underlying Oblivious Evaluation of Extended Permutation (OEP) and secure 2-party computation (2PC) protocols, and yields a more than 40% reduction in overall communication cost (the computation time is also slightly decreased and the number of rounds remains unchanged).
Development of computing devices with the proliferation of the Internet has prompted enormous opportunities for cooperative computation. These computations could occur between trusted or partially trusted partners, or even between competitors. Secure multi-party computation (MPC) protocols allow two or more parties to collaborate and compute a public functionality using their private inputs without the need for a trusted third-party. However, the generic solutions for MPC are not adequate for some particular cases where the function itself is also sensitive and required to be kept private. Private function evaluation (PFE) is a special case of MPC, where the function to be computed is known by only one party. PFE is useful in several real-life applications where an algorithm or a function itself needs to remain secret for reasons such as protecting intellectual property or security classification level. Recently, designing efficient PFE protocols have been a challenging and attractive task for cryptography researchers. iv In this dissertation, we mainly focus on improving two-party private function evaluation (2PFE) schemes. Our primary goal is enhancing the state-of-the-art by designing secure and cost-efficient 2PFE protocols for both symmetric and asymmetric cryptography based solutions. In this respect, we first aim to improve 2PFE protocols based on (mostly) symmetric cryptographic primitives. We look back at the seminal PFE framework presented by Mohassel and Sadeghian at Eurocrypt'13. We show how to adapt and utilize the well-known half gates garbling technique (Zahur et al., Eurocrypt'15) to their constant round 2PFE scheme. Compared to their scheme, our resulting optimization significantly improves both underlying oblivious extended permutation (OEP) and secure 2-party computation (2PC) protocols, and yields a more than 40% reduction in overall communication cost. We next propose a novel and highly efficient 2PFE scheme based on the decisional Di e-Hellman (DDH) assumption. Our scheme consists of two protocols, one is utilized in the initial execution, and the other is in the subsequent runs. One of the novelties of our scheme over the state-of-the-art is that it results in a significant cost reduction when the same private function is evaluated more than once between the same or varying parties. To the best of our knowledge, this is the most efficient and the first 2PFE scheme that enjoys reusability feature. Our protocols achieve linear communication and computation complexities, and a constant number of rounds which is at most three (depending on the size of the inputs of the party that holds the function).
Outsourced secure multiparty computation (SMC) protocols allow resource-constrained devices to execute input-private computation with great efficiency. Unfortunately, existing outsourced SMC protocols require that all parties know the function being evaluated, precluding applications where the function itself must remain private. We develop the first linear-complexity protocols for outsourcing private function evaluation (PFE), SMC protocols that provide input and function privacy. Assuming a semi-honest function holder, we build on existing two-party PFE constructions to develop outsourced protocols that are secure against a semi-honest, covert, or malicious outsourcing server and malicious mobile participants. To do this, we develop a garbling technique for combining public and private sub-circuits in a single computation. This allows us to apply auxiliary checks for malicious behaviour using only free-XOR gates. These protocols demonstrate the feasibility of outsourced PFE and provide a first step towards privacy-preserving applications for use in cloud computing.