International Association
for Cryptologic Research

Secure computation enables n mutually distrustful parties to compute a function over their private inputs jointly. In 1988, Ben-Or, Goldwasser, and Wigderson (BGW) proved that any function can be computed with perfect security in the presence of a malicious adversary corrupting at most $$t< n/3$$ t < n / 3 parties. After more than 30 years, protocols with perfect malicious security, and round complexity proportional to the circuit’s depth, still require (verifiably) sharing a total of $$O(n^2)$$ O ( n 2 ) values per multiplication. In contrast, only O ( n ) values need to be shared per multiplication to achieve semi-honest security. Sharing $$\Omega (n)$$ Ω ( n ) values for a single multiplication seems to be the natural barrier for polynomial secret-sharing-based multiplication. In this paper, we construct a new secure computation protocol with perfect, optimal resilience and malicious security that incurs (verifiably) sharing O ( n ) values per multiplication. Our protocol requires a constant number of rounds per multiplication. Like BGW, it has an overall round complexity that is proportional only to the multiplicative depth of the circuit. Our improvement is obtained by a novel construction for weak VSS for polynomials of degree 2t , which incurs the same communication and round complexities as the state-of-the-art constructions for VSS for polynomials of degree t . Our second contribution is a method for reducing the communication complexity for any depth 1 sub-circuit to be proportional only to the size of the input and output (rather than the size of the circuit). This implies protocols with sub-linear communication complexity (in the size of the circuit) for perfectly secure computation for important functions like matrix multiplication.

Many recent private set intersection (PSI) protocols encode input sets as polynomials. We consider the more general notion of an oblivious key-value store (OKVS), which is a data structure that compactly represents a desired mapping $k_i$ to $v_i$. When the $v_i$ values are random, the OKVS data structure hides the $k_i$ values that were used to generate it. The simplest (and size-optimal) OKVS is a polynomial $p$ that is chosen using interpolation such that $p(k_i)=v_i$. We initiate the formal study of oblivious key-value stores, and show new constructions resulting in the fastest OKVS to date. Similarly to cuckoo hashing, current analysis techniques are insufficient for finding *concrete* parameters to guarantee a small failure probability for our OKVS constructions. Moreover, it would cost too much to run experiments to validate a small upperbound on the failure probability. We therefore show novel techniques to amplify an OKVS construction which has a failure probability $p$, to an OKVS with a similar overhead and failure probability $p^c$. Setting $p$ to be moderately small enables to validate it by running a relatively small number of $O(1/p)$ experiments. This validates a $p^c$ failure probability for the amplified OKVS. Finally, we describe how OKVS can significantly improve the state of the art of essentially all variants of PSI. This leads to the fastest two-party PSI protocols to date, for both the semi-honest and the malicious settings. Specifically, in networks with moderate bandwidth (e.g., 30 - 300 Mbps) our malicious two-party PSI protocol has 40\% less communication and is 20-40% faster than the previous state of the art protocol, even though the latter only has heuristic confidence.

Secure computation enables $n$ mutually distrustful parties to compute a function over their private inputs jointly. In 1988 Ben-Or, Goldwasser, and Wigderson (BGW) demonstrated that any function can be computed with perfect security in the presence of a malicious adversary corrupting at most $t< n/3$ parties. After more than 30 years, protocols with perfect malicious security, with round complexity proportional to the circuit's depth, still require sharing a total of $O(n^2)$ values per multiplication. In contrast, only $O(n)$ values need to be shared per multiplication to achieve semi-honest security. Indeed sharing $\Omega(n)$ values for a single multiplication seems to be the natural barrier for polynomial secret sharing-based multiplication. In this paper, we close this gap by constructing a new secure computation protocol with perfect, optimal resilience and malicious security that incurs sharing of only $O(n)$ values per multiplication, thus, matching the semi-honest setting for protocols with round complexity that is proportional to the circuit depth. Our protocol requires a constant number of rounds per multiplication. Like BGW, it has an overall round complexity that is proportional only to the multiplicative depth of the circuit. Our improvement is obtained by a novel construction for {\em weak VSS for polynomials of degree-$2t$}, which incurs the same communication and round complexities as the state-of-the-art constructions for {\em VSS for polynomials of degree-$t$}. Our second contribution is a method for reducing the communication complexity for any depth-1 sub-circuit to be proportional only to the size of the input and output (rather than the size of the circuit). This implies protocols with \emph{sublinear communication complexity} (in the size of the circuit) for perfectly secure computation for important functions like matrix multiplication.

We present a 2-party private set intersection (PSI) protocol which provides security against malicious participants, yet is almost as fast as the fastest known semi-honest PSI protocol of Kolesnikov et al. (CCS 2016). Our protocol is based on a new approach for two-party PSI, which can be instantiated to provide security against either malicious or semi-honest adversaries. The protocol is unique in that the only difference between the semi-honest and malicious versions is an instantiation with different parameters for a linear error-correction code. It is also the first PSI protocol which is concretely efficient while having linear communication and security against malicious adversaries, while running in the OT-hybrid model (assuming a non-programmable random oracle). State of the art semi-honest PSI protocols take advantage of cuckoo hashing, but it has proven a challenge to use cuckoo hashing for malicious security. Our protocol is the first to use cuckoo hashing for malicious- secure PSI. We do so via a new data structure, called a probe-and-XOR of strings (PaXoS), which may be of independent interest. This abstraction captures important properties of previous data structures, most notably garbled Bloom filters. While an encoding by a garbled Bloom filter is larger by a factor of $\Omega(\lambda)$ than the original data, we describe a significantly improved PaXoS based on cuckoo hashing that achieves constant rate while being no worse in other relevant efficiency measures.

We present a new protocol for computing a circuit which implements the private set intersection functionality (PSI). Using circuits for this task is advantageous over the usage of specific protocols for PSI, since many applications of PSI do not need to compute the intersection itself but rather functions based on the items in the intersection.Our protocol is the first circuit-based PSI protocol to achieve linear communication complexity. It is also concretely more efficient than all previous circuit-based PSI protocols. For example, for sets of size $$2^{20}$$ it improves the communication of the recent work of Pinkas et al. (EUROCRYPT’18) by more than 10 times, and improves the run time by a factor of 2.8x in the LAN setting, and by a factor of 5.8x in the WAN setting.Our protocol is based on the usage of a protocol for computing oblivious programmable pseudo-random functions (OPPRF), and more specifically on our technique to amortize the cost of batching together multiple invocations of OPPRF.

Recently, there has been huge progress in the field of concretely efficient secure computation, even while providing security in the presence of malicious adversaries. This is especially the case in the two-party setting, where constant-round protocols exist that remain fast even over slow networks. However, in the multi-party setting, all concretely efficient fully secure protocols, such as SPDZ, require many rounds of communication. In this paper, we present a constant-round multi-party secure computation protocol that is fully secure in the presence of malicious adversaries and for any number of corrupted parties. Our construction is based on the constant-round protocol of Beaver et al. (the BMR protocol) and is the first version of that protocol that is concretely efficient for the dishonest majority case. Our protocol includes an online phase that is extremely fast and mainly consists of each party locally evaluating a garbled circuit. For the offline phase, we present both a generic construction (using any underlying MPC protocol) and a highly efficient instantiation based on the SPDZ protocol. Our estimates show the protocol to be considerably more efficient than previous fully secure multi-party protocols.

The random-access memory model of computation allows program constant-time memory lookup and is more applicable in practice today, covering many important algorithms. This is in contrast to the classic setting of secure 2-party computation (2PC) that mostly follows the approach for which the desired functionality must be represented as a Boolean circuit. In this work, we design the first constant-round maliciously secure two-party protocol in the RAM model. Our starting point is the garbled RAM construction of Gentry et al. (EUROCRYPT, pp 405–422, 2014) that readily induces a constant round semi-honest two-party protocol for any RAM program assuming identity-based encryption schemes. We show how to enhance the security of their construction into the malicious setting while facing several challenges that stem due to handling the data memory. Next, we show how to apply our techniques to a more recent garbled RAM construction by Garg et al. (STOC, pp 449–458, 2015) that is based on one-way functions.

We describe a novel approach for two-party private set intersection (PSI) with semi-honest security. Compared to existing PSI protocols, ours has a more favorable balance between communication and computation. Specifically, our protocol has the lowest monetary cost of any known PSI protocol, when run over the Internet using cloud-based computing services (taking into account current rates for CPU + data). On slow networks (e.g., 10 Mbps) our protocol is actually the fastest.Our novel underlying technique is a variant of oblivious transfer (OT) extension that we call sparse OT extension. Conceptually it can be thought of as a communication-efficient multipoint oblivious PRF evaluation. Our sparse OT technique relies heavily on manipulating high-degree polynomials over large finite fields (i.e. elements whose representation requires hundreds of bits). We introduce extensive algorithmic and engineering improvements for interpolation and multi-point evaluation of such polynomials, which we believe will be of independent interest.Finally, we present an extensive empirical comparison of state-of-the-art PSI protocols in several application scenarios and along several dimensions of measurement: running time, communication, peak memory consumption, and—arguably the most relevant metric for practice—monetary cost.

We present a new multiparty computation protocol secure against a static and malicious dishonest majority. Unlike most previous protocols that were based on working on MAC-ed secret shares, our approach is based on computations on homomorphic commitments to secret shares. Specifically we show how to realize MPC using any additively-homomorphic commitment scheme, even if such a scheme is an interactive two-party protocol.Our new approach enables us to do arithmetic computation over arbitrary finite fields. In addition, since our protocol computes over committed values, it can be readily composed within larger protocols, and can also be used for efficiently implementing committing OT or committed OT. This is done in two steps, each of independent interest:1.Black-box extension of any (possibly interactive) two-party additively homomorphic commitment scheme to an additively homomorphic multiparty commitment scheme, only using coin-tossing and a “weak” equality evaluation functionality.2.Realizing multiplication of multiparty commitments based on a lightweight preprocessing approach. Finally we show how to use the fully homomorphic commitments to compute any functionality securely in the presence of a malicious adversary corrupting any number of parties.

In the setting of secure computation, a set of parties wish to compute a joint function of their private inputs without revealing anything but the output. Garbled circuits, first introduced by Yao, are a central tool in the construction of protocols for secure two-party computation (and other tasks like secure outsourced computation), and are the fastest known method for constant-round protocols. In this paper, we initiate a study of garbling multivalent-logic circuits, which are circuits whose wires may carry values from some finite/infinite set of values (rather than only $$\mathsf {True}$$True and $$\mathsf {False}$$False). In particular, we focus on the three-valued logic system of Kleene, in which the admissible values are $$\mathsf {True}$$True, $$\mathsf {False}$$False, and $$\mathsf {Unknown}$$Unknown. This logic system is used in practice in SQL where some of the values may be missing. Thus, efficient constant-round secure computation of SQL over a distributed database requires the ability to efficiently garble circuits over 3-valued logic. However, as we show, the two natural (naive) methods of garbling 3-valued logic are very expensive.In this paper, we present a general approach for garbling three-valued logic, which is based on first encoding the 3-value logic into Boolean logic, then using standard garbling techniques, and final decoding back into 3-value logic. Interestingly, we find that the specific encoding chosen can have a significant impact on efficiency. Accordingly, the aim is to find Boolean encodings of 3-value logic that enable efficient Boolean garbling (i.e., minimize the number of AND gates). We also show that Boolean AND gates can be garbled at the same cost of garbling XOR gates in the 3-value logic setting. Thus, it is unlikely that an analogue of free-XOR exists for 3-value logic garbling (since this would imply free-AND in the Boolean setting).