We consider a minimal scenario for secure computation: Parties A and B have private inputs x and y and a shared random string r.A and B are each allowed to send a single message to a third party C, from which C is to learn the value of ~(z, y) for some function ~, but nothing else.We show that this model is surpris-Permission to copywithout fee all or part of this material is granted provided that the copies are not made or distributed for direct eommarcial advantaqe, tha ACM copyrioht notice a?d the title of the publicatiort 'and Its date appear, and notice is gwen that copying is by permission of the Association of Computing Machinery.
We consider a minimal scenario for secure computation: Parties A and B have private inputs x and y and a shared random string r.A and B are each allowed to send a single message to a third party C, from which C is to learn the value of ~(z, y) for some function ~, but nothing else.We show that this model is surpris-Permission to copywithout fee all or part of this material is granted provided that the copies are not made or distributed for direct eommarcial advantaqe, tha ACM copyrioht notice a?d the title of the publicatiort 'and Its date appear, and notice is gwen that copying is by permission of the Association of Computing Machinery.
We consider a minimal scenario for secure computation: Parties A and B have private inputs x and y and a shared random string r. A and B are each allowed to send a single message to a third party C, from which C is to learn the value of f(x, y) for some function f, but nothing else. We show that this model is surprisingly powerful: every function f can be securely computed in this fashion. If the messages are required to be of polynomial size, then we exhibit an efficient protocol for any function f computable in nondeterministic logspace. Using a computational notion of security, we exhibit efficient protocols for any polynomial-time computable function f, assuming the existence of one-way functions. The above results generalize to the case where there are more than two parties with private inputs. The minimalistic nature of our model makes it easy to transform positive results achieved in our model to other more general models of secure computation. It also gives hope for lowerbound proofs. We give an alternative characterization of our model in terms of graph embeddings, and use this to show that for most Boolean functions on {0, 1} n × {0, 1} n, the need to hide just one of the input bits from C requires a communication overhead of n bits. 1
We consider secure computation of randomized functions by two users, where both the users (Alice and Bob) have inputs, Alice sends a message to Bob over a rate-limited, noise-free link, and then Bob produces the output. We study this problem when privacy is required only against Bob, i.e., from the message, Bob must not learn any information about Alice's input other than what can be inferred by his own input and output. We give a single-letter expression for the optimal rate. We also explicitly characterize securely computable randomized functions when input has full support, which leads to a much simpler expression for the optimal rate. Recently, Data (ISIT 2016) studied the other two cases (first, when privacy is required against both the users; and second, when privacy is required only against Alice) and obtained single-letter expressions for optimal rates in both the scenarios. Yassaee, Gohari, and Aref (IEEE Transactions on Information Theory 2015) studied the case when there is no privacy requirement and obtained a single-letter expression for the optimal rate, when Alice and Bob interact for arbitrary but finite number of rounds, and both of them may produce potentially different outputs.
It seems to be a generally acknowledged fact that you should never trust a computer and that you should trust the person operating the computer even less. This in particular becomes a problem when the party that you do not trust is one which is separated from you and is one on which you depend, e.g. because that party is the holder of some data or some capability that you need in order to operate correctly. How do you perform a given task involving interaction with other parties while allowing these parties a minimal influence on you and, if privacy is an issue, allowing them to learn as little about you as possible. This is the general problem of secure multiparty computation. The usual way of formalizing the problem is to say that a number of parties who do not trust each other wish to compute some function of their local inputs, while keeping their inputs as secret as possible and guaranteeing the correctness of the output. Both goals should be obtained even if some parties stop participating or some malevolent coalition of the parties start deviating arbitrarily from the agreed protocol. The task is further complicated by the fact that besides their mutual distrust, nor do the parties trust the channels by which they communicate. A general solution to the secure multiparty computation problem is a compiler which given any feasible function describes an efficient protocol which allows the parties to compute the function securely on their local inputs over an open network. Over the past twenty years the secure multiparty computation problem has been the subject of a large body of research, both research into the models of multiparty computation and research aimed at realizing general secure multiparty computation. The main approach to realizing secure multiparty computation has been based on verifiable secret sharing as computation, where each party holds a secret share of each input and during the execution computes secret shares of all intermediate values. This approach allows the parties to keep all inputs and intermediate values secret and to pool the shares of the output values to learn exactly these values. More recently an approach based on joint homomorphic encryption was introduced, allowing for an efficient realization of general multiparty computation secure against an eavesdropper. A joint encryption scheme is an encryption scheme where all parties can encrypt, but where it takes the participation of all parties to open an encryption. The computation then starts by all parties broadcasting encryptions of their inputs and progresses through computing encryptions of the intermediary values using the homomorphic properties of the encryption scheme. The encryptions of the outputs can then be jointly decrypted. In this dissertation we extend this approach by using threshold homomorphic encryption to provide full-fledged security against an active attacker which might control some of the parties and which might take over parties during the course of the protocol execution. As opposed to a joint encryption scheme a threshold encryption scheme only requires that a given number of the parties are operating correctly for decryption to be possible. In this dissertation we show that threshold homomorphic encryption allows to solve the secure general multiparty computation problem more efficiently than previous approaches to the problem. Starting from an open point-to-point network there is a long way to general secure multiparty computation. The dissertation contains contributions at several points along the way. In particular we investigate how to realize secure channels. We also show how threshold signature schemes can be used to efficiently realize a broadcast channel and how threshold cryptography can be used to provide the parties of the network with a source of shared randomness. All three tools are well-known to be extremely powerful resources in a network, and our principle contribution is to provide efficient realizations. The dissertation also contains contributions to the definitional part of the field of multiparty computation. Most significantly we augment the recent model of universally composable security with a formal notion of what it means for a protocol to only realize a given problem under a given restricted input-output behavior of the environment. This e.g. allows us to give the first specification of a universally composable zero-knowledge proof of membership which does not at the same time require the proof system to be a proof of knowledge.
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.
We consider the problem of Non-Interactive Two-Party Secure Computation (NISC), where Rachel wishes to publish an encryption of her input x, in such a way that any other party, who holds an input y, can send her a single message which conveys to her the value f(x, y), and nothing more. We demand security against malicious parties. While such protocols are easy to construct using garbled circuits and general non-interactive zero-knowledge proofs, this approach inherently makes a non-black-box use of the underlying cryptographic primitives and is infeasible in practice.
The goal of secure two-party computation is to enable two parties to cooperatively evaluate a function that takes private data from both parties as input without exposing any of the private data. At the end of the computation, the participants learn nothing more than the output of the function. The two-party secure computation systems have three properties: (1) the application involves inputs from two independent parties; (2) each party wants to keep its own data secret; and (3) the participants agree to reveal the output of the computation. That is, the result itself does not imply too much information about either party's private input. Informally, the security requirements are that nothing is learned from the protocol other than the output (privacy), and that the output is distributed according to the prescribed functionality (correctness). The threat models in the two-party computation assume the presence of three different types of adversaries: 1) Semi honest, 2) Malicious and 3) Covert.