In this chapter, we formally define multiparty computation tasks and the security of protocols realizing them. We give a broad presentation of the existing constructions of secure multiparty computation (SMC) protocols and explain why they are correct and secure. We discuss the different environmental aspects of SMC protocols and explain the requirements that are necessary and sufficient for their existence.
In this chapter, we formally define multiparty computation tasks and the security of protocols realizing them. We give a broad presentation of the existing constructions of secure multiparty computation (SMC) protocols and explain why they are correct and secure. We discuss the different environmental aspects of SMC protocols and explain the requirements that are necessary and sufficient for their existence.
Secure multiparty computation (SMC) allows a set of parties to jointly compute a function on private inputs such that, they learn only the output of the function, and the correctness of the output is guaranteed even when a subset of the parties is controlled by an adversary. SMC allows data to be kept in an uncompromisable form and still be useful, and it also gives new meaning to data ownership, allowing data to be shared in a useful way while retaining its privacy. Thus, applications of SMC hold promise for addressing some of the security issues information-driven societies struggle with. In this thesis, we implement two SMC protocols. Our primary objective is to gain a solid understanding of the basic concepts related to SMC. We present a brief survey of the field, with focus on SMC based on secret sharing. In addition to the protocol im- plementations, we implement circuit randomization, a common technique for efficiency improvement. The implemented protocols are run on a simulator to securely evaluate some simple arithmetic functions, and the round complexities of the implemented protocols are compared. Finally, we attempt to extend the implementation to support more general computations.
In this paper, comparative study of different available Secure Multiparty Computation (SMC) protocols have been addressed. In SMC, a set of parties wishes to jointly compute some function on their inputs. This computation must preserve certain security properties, like privacy and correctness. The general approach for such kind of computation is to make use of trusted third party to do the computation and then announce the result publicly. The major problem with this approach is that it is difficult to find a third party which is trusted by all the parties providing the inputs. This implies that the data of parties must be secured. Security is meant to achieve correctness of the result of computation and keeping the party’s input private even if some of the parties are corrupted.
Secure Multiparty Computation technique plays an important role in the security research of distributed systems.This paper firstly summarizes the advances in theoretical and practical studies on SMC,and then analysis the basic protocols and its related cryptographic algorithms.Secondly,the key tools,secret share,homomorphic public key cryptography,mix network,zero knowledge proof,oblivious transfer and private comparison protocol in implementation SMC are studied deeply.Finally,some research directions in this area are also proposed.
Secure Multiparty Computation (abrv. MPC) is a group of techniques that enable multiple entities to compute some function on their private inputs. Moreformally,itenablesasetofplayers{P1,...,Pn},eachofthemholding private inputs xi, where i is the index of the player, to evaluate a function f(x1,...,xn) = (y1,...,yn) so that every player Pi learns yi. Multiparty Computation has many application scenarios such as private auctioning, computation outsourcing, or private information retrieval. These and other applications make MPC a very appealing object of study, since it may be a solution to problems in different fields. The objective of this thesis is twofold. First, we aim to provide a comprehensive guide to the current state of multiparty computation protocols. Wedosobyinspectingthetwocategorieswheremostgeneralfunctionality secure function evaluation protocols are inserted - boolean or arithmetic circuit evaluation. Moreover, we show how to implement MPC protocols with current constructions, and what problems are inherently connected to the chosen representations. Second, we document some of the design choices behind a partial implementation of a concrete secure arithmetic circuit evaluation protocol - the SPDZ protocol by Damgård et al. [10]. We explain the protocol in general terms, and then go into the details of some subprotocols, namely those that were implemented.
In this chapter we present the Arithmetic Black Box (ABB) functionality. It is an ideal functionality that preserves the privacy of the data it stores and allows computations to be performed on the data stored, as well as retrieve certain pieces of data. We show that it is a very convenient abstraction of secure multiparty computation (SMC), which enables easy extensions and the construction of large privacy-preserving applications on top of it. In this chapter, we give a detailed definition of the ABB functionality and present different ways in which it can be implemented securely. We explain what extending an ABB means and how it is integrated into larger applications.
Secure multi-party computation is a conceptual framework in which distrusting parties engage in a protocol to securely perform a computational task. Depending on the precise model of security, different sets of tasks admit secure protocols. We take a complexity-theoretic approach to studying the inherent difficulty of securely realizing tasks in various standard security models. * We give the first alternate characterization of secure realizability in the framework of universally composable (UC) security. This is the first characterization in any model to consider completely arbitrary computational tasks and completely arbitrary communication channels. * The most long-standing class of computational tasks studied are those in which two parties evaluate a deterministic function. For these tasks, we give the first complete, combinatorial characterizations of secure realizability in the passive, standalone, and universally composable security models, against computationally unbounded adversaries. * Say that a task G has ``as much cryptographic complexity'' as another task F if there is a secure protocol for F that uses access to a secure implementation of G. We show that there is an infinite hierarchy of tasks with strictly increasing cryptographic complexities, with respect to computationally unbounded security. We also show that there exist tasks whose cryptographic complexities are incomparable. * In contrast, we show that under a standard cryptographic assumption, there exist only two distinct levels of cryptographic complexity with respect to polynomial-time security. Every task either has a trivial protocol using plain communication channels, or is complete (i.e., given access to a secure implementation of this task, there are secure protocols for all other tasks). This is the first result to derive a characterization of completeness for a class of arbitrary interactive tasks. In light of these characterizations, the only tasks which are securely realizable in the demanding framework of universal composition are those related to secure communication. Indeed, the framework has been used to define the security of encryption schemes, which has allowed for modular design and analysis of protocols. We consider a similar approach for homomorphic encryption schemes. A homomorphic scheme is one in which anyone can obtain an encryption of f(m_1, ..., m_n), given only the encryptions of unknown messages m_1, ..., m_n, for a specific set of functions f. * We give a construction of a homomorphic encryption scheme in which the allowed homomorphic operation is as full-featured as possible --- namely, one can derive a correctly-distributed encryption of f(m) given an encryption of unknown message m, for some functions f --- yet it is computationally infeasible to generate a ciphertext that is related to other ciphertexts in any other way. Our contributions involve developing new appropriate security definitions as well as new constructions. * We show that schemes with such powerful security guarantees can be used to build conceptually simple, efficient, UC-secure protocols for verifiable computations on encrypted data. We show protocols for two tasks related to aggregating encrypted data.