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).
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).
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).
Private function evaluation aims to securely compute a functionf(x1,…,xn)without leaking any information other than what is revealed by the output, wherefis a private input of one of the parties (sayParty1) andxiis a private input of theith partyPartyi. In this article, we propose a novel and securetwo-party private function evaluation(2PFE) scheme based on the DDH assumption. Our scheme introduces a reusability feature that significantly improves the state-of-the-art. Accordingly, our scheme has two variants, one is utilized in the initial execution of the functionf, and the other is utilized in its subsequent evaluations. To the best of our knowledge, this is the first and most efficient 2PFE scheme that enjoys a reusablity feature. Our protocols achieve linear communication and computation complexities and a constant number of rounds which is at most three.
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).
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
Multiparty Computation (hereafter MPC) is a technique for allowing a set ofparticipants to run a secure computation with the assurance that the output is (1) correct, and (2) that a malicious party did not learn anything about the inputs of the honest parties besides what it can glean from the output. Impor- tantly much of cryptography is based on the assumption that an honest party has a private and secret input, and if the adversary learns this input the security of the scheme is broken. Then naturally the techniques of MPC can be applied to create threshold protocols for these cryptographic schemes to ensure that the secret inputs are not leaked and moreover that no group of parties smaller than the threshold know the input at all. While we have known how to generically evaluate MPC for any function since the 80s the question of efficiency still drives progress to this day. This thesis looks at two approaches for making secure com- putation more practical to deploy: developing specialized protocols for appli- cations such as distributed key generation and signing with RSA and ECDSA; and improving the state of the art of maliciously secure generic boolean-circuit MPC. We first look at work that produced a distributed key generation protocol for RSA that utilizes a novel candidate sampling mechanism to reduce waste in primality testing. The second work builds a threshold scheme for symmetric cryptographic primitives such as AES and SHA where there is limited algebraic structure to exploit by efficiently converting a generic n-of-n MPC protocol into a threshold t-of-n MPC protocol. Future directions in this thesis are in combin- ing techniques from the prior works to create a blind signature scheme for the Elliptic Curve Digital Signature Algorithm (ECDSA) that requires both alge- braic operations over elliptic curves and additionally symmetric evaluations of the SHA2 hash function.--Author's abstract