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Allerton Conference on Communication, Control, and Computing

Communication requirements for secure computation

Deepesh Data, Vinod M. Prabhakaran

Published Oct 1, 2013• 2 citations
Publisher

Abstract

The question of whether and how mutually distrusting parties can collaborate is a central theme in cryptography. The goal of secure function computation is to ensure that parties may correctly compute functions of their data without learning additional information. A remarkable result of Ben Or, Goldwasser, and Wigderson from 1988 shows that it is possible for parties connected by pairwise, private, noise-free links to compute functions with zero error and perfect information theoretic security provided the number of parties who may collude meets a certain threshold; specifically, if the colluders form a strict minority for the honest-but-curious model and they are strictly less than a third for the malicious model. In this paper we provide basic lowerbounds on the amount of communication required to compute with zero-error and perfect security in a three-party setting under the honest-but-curious model.

DOI
10.1109/allerton.2013.6736526

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The question of whether and how mutually distrusting parties can collaborate is a central theme in cryptography. The goal of secure function computation is to ensure that parties may correctly compute functions of their data without learning additional information. A remarkable result of Ben Or, Goldwasser, and Wigderson from 1988 shows that it is possible for parties connected by pairwise, private, noise-free links to compute functions with zero error and perfect information theoretic security provided the number of parties who may collude meets a certain threshold; specifically, if the colluders form a strict minority for the honest-but-curious model and they are strictly less than a third for the malicious model. In this paper we provide basic lowerbounds on the amount of communication required to compute with zero-error and perfect security in a three-party setting under the honest-but-curious model.
In secure multiparty computation (MPC), mutually distrusting users collaborate to compute a function of their private data without revealing any additional information about their data to the other users. While it is known that information theoretically secure MPC is possible among n users having access to private randomness and are pairwise connected by secure, noiseless, and bidirectional links against the collusion of less than n/2 users (in the honest-but-curious model; the threshold is n/3 in the malicious model), relatively little is known about the communication and randomness complexity of secure computation, i.e., the amount of communication and randomness required to compute securely. In this paper, we employ information theoretic techniques to obtain lower bounds on communication and randomness complexity of secure MPC. We restrict ourselves to a concrete interactive setting involving three users under which all functions are securely computable against corruption of individual users in the honest-but-curious model. We derive lower bounds for both the perfect security case (i.e., zero-error and no leakage of information) and asymptotic security (where the probability of error and information leakage vanish as block-length goes to ∞). Our techniques include the use of a data processing inequality for residual information (i.e., the gap between mutual information and Gács-Körner common information), a new information inequality for three-user protocols, and the idea of distribution switching by which lower bounds computed under certain worst case scenarios can be shown to apply for the general case. Our lower bounds are shown to be tight for various functions of interest. In particular, we show concrete functions which have communication-ideal protocols, i.e., which achieve the minimum communication simultaneously on all links in the network. Also, we obtain the first explicit example of a function that incurs a higher communication cost than the input length, in the secure computation model of Feige et al. (26th Annual ACM Symposium on Theory of Computing, 1994), who had shown that such functions exist. We also show that our communication bounds imply tight lower bounds on the amount of randomness required by MPC protocols for many interesting functions.
In information theoretically secure multiparty computation, several mutually distrusting users want to jointly compute a function of their private data such that users do not learn any additional information about other users' data other than what they can infer from their own data and the function value they compute. In this work we consider asymptotically secure computation - where vanishing probability of error and vanishing information leakage are allowed as block lengths become large - in a three user setting, where two users have inputs and third user securely computes the output of a function on these two inputs. We provide generic lower bounds on the amount of communication required among users and the total amount of private randomness needed to compute any function in this three-user model. We also consider some examples where our bounds are tight. Our lower bounds are derived for the honest-but-curious security model and hence also apply for the malicious model.
In the setting of secure multiparty computation, several distrustful parties wish to carry out a distributed computing task on their local private data while satisfying several security properties such as correctness, privacy, independence of inputs and fairness. The aim of secure multiparty computation (MPC) is to enable the parties to carry out the computation in a secure manner, eliminating any attempt of an adversarial entity to harm the execution. The concept of secure computation is very general and fundamental in cryptography, and models any distributed computing task, including simple computations as coin-tossing and broadcast, as well as more complex tasks such as electronic auctions and anonymous transactions. In this thesis, we study two foundational aspects of secure computation: perfect security and fairness. In the first part of this thesis, we study perfect security in secure computation. A protocol that is perfectly secure cannot be broken even when the adversary has unlimited computational power and its security holds unconditionally. One of the most fundamental results of secure computation was presented by Ben-Or, Goldwasser and Wigderson (BGW) in 1988. They demonstrated that any n-party functionality can be computed with perfect security, in the private channels model. When the adversary is semi-honest this holds as long as t < n/2 parties are corrupted, and when the adversary is malicious this holds as long as t < n/3 parties are corrupted. Unfortunately, a full proof of these results was never published. In this thesis, we remedy this situation and provide a full proof of security of the BGW protocol. This also includes a full description of the protocol for the malicious setting. In addition to the above, we observe that by some simple and natural modifications, the BGW protocol can be significantly simplified and one of its expensive (and perhaps most complicated) subprotocols can be saved. We present a new multiplication protocol that is based on the original construction, but is simpler and achieves higher efficiency. In the second part of this thesis, we study fairness in secure two party computation. Informally, the fairness property guarantees that if one party receives its output, then the other party does too. The well-known impossibility result of Cleve (STOC 1986) implies that, in general, it is impossible to securely compute a function with complete fairness without an honest majority. Until recently, the accepted belief has been that nothing non-trivial can be computed with complete fairness in the two party setting. The surprising work of Gordon, Hazay, Katz and Lindell (STOC 2008) shows that this belief is false, and that there exist some non-trivial (deterministic, finite-domain) Boolean functions that can be computed fairly. This raises the fundamental question of characterizing complete fairness in secure two-party computation. We focus on this question and give both positive and negative results. We first characterize
In secure multiparty computation, mutually distrusting users in a network want to collaborate to compute functions of data which is distributed among the users. The users should not learn any additional information about the data of others than what they may infer from their own data and the functions they are computing. Previous works have mostly considered the worst case context (i.e., without assuming any distribution for the data); Lee and Abbe (2014) is a notable exception. Here, we study the average case (i.e., we work with a distribution on the data) where correctness and privacy is only desired asymptotically. For concreteness and simplicity, we consider a secure version of the function computation problem of Körner and Marton (1979) where two users observe a doubly symmetric binary source with parameter p and the third user wants to compute the XOR. We show that the amount of communication and randomness resources required depends on the level of correctness desired. When zero-error and perfect privacy are required, the results of Data et al. (2014) show that it can be achieved if and only if a total rate of 1 bit is communicated between every pair of users and private randomness at the rate of 1 is used up. In contrast, we show here that, if we only want the probability of error to vanish asymptotically in blocklength, it can be achieved by a lower rate (binary entropy of p) for all the links and for private randomness; this also guarantees perfect privacy. We also show that no smaller rates are possible even if privacy is only required asymptotically.
The problem of three-party secure computation, where a function of private data of two parties is to be computed by a third party without revealing information beyond respective inputs or outputs is considered. New and better lower bounds on the amount of communication required between the parties to guarantee zero probability of error in the computation and achieve information-theoretic security are derived. Protocols are presented and proved to be optimal in some cases by showing that they achieve the improved lower bounds.
The notion of secure computation is central to cryptography. Introduced in the seminal works of Yao [FOCS'82, FOCS'86] and Goldreich, Micali and Wigderson [STOC'87], secure multiparty computation allows a group of (mutually) distrustful parties to jointly compute any functionality over their individual private inputs in such a manner that the honest parties obtain the correct outputs and no group of malicious parties learn anything beyond their inputs and the prescribed outputs. General feasibility results for secure computation were given by Yao [FOCS'86] and Goldreich et al. [STOC'87] more than two decades ago. Subsequent to these works, designing secure computation protocols that can tolerate more powerful adversaries and satisfy stronger notions of security has been a very active area of research. In this dissertation, we study two such new frontiers in the area of secure computation. In the first part of this dissertation, we initiate a study of designing leakage-resilient interactive protocols. Specifically, we consider the scenario where an adversary, in addition to corrupting a subset of parties, can leak (potentially via physical attacks) arbitrary information from the secret state of any honest party. This is in contrast to the standard notion of secure computation where it is assumed that the adversary only has black-box'' access to the honest parties. In particular, we formalize a meaningful definition of leakage-resilient zero knowledge proof systems and provide constructions that satisfy our notion. We also discuss various applications of our results. The second part of this dissertation concerns with the general question of whether it is possible to securely run cryptographic protocols over an insecure network environment such as the Internet. It is well-known that the standard notion of secure computation is only relevant to the stand-alone setting where a single protocol is being executed in isolation; as such it does not guarantee security when multiple protocol sessions may be executed concurrently under the control of an adversary who is present across all sessions. We consider the open problem of constructing secure password-based authenticated key exchange protocols in such a setting in the plain model (i.e., without assuming any trusted infrastructure or random oracles). We give the first construction of such a protocol based on standard cryptographic assumptions. Our results are in fact much more general, and extend to other functionalities w.r.t. a (necessarily) weakened notion of concurrently secure computation. The results presented in this dissertation stem from two papers which are joint works with Sanjam Garg and Amit Sahai, and with Vipul Goyal and Rafail Ostrovsky, respectively.