Secure multiparty computation (MPC) enables parties to compute an arbitrary function without revealing each party's inputs. A typical MPC is secret-sharing based MPC (SS-MPC). In the SS-MPC, each party distributes its inputs, and the computation proceeds with secret shares that look exactly like random numbers distributed among the parties. In the SS-MPC protocol, the parties can compute any function represented as a circuit by using shares locally and communicating among the parties. In particular, when the parties compute a complex function composed of binary and arithmetic circuits, an efficient share conversion protocol facilitates the computation of it. An important conversion protocol is a bit-composition protocol that converts a k-dimensional vector with shares on ℤ2 (i.e., shares of binary sequence) to shares on ℤ2k (i.e., shares of decimal value). Previous studies proposed a maliciously secure bit-composition protocol with robustness, which is a security notion that all parties learn the correct output regardless of the attacker's behaviour. However, its security is dependent on a statistical parameter or proved in the random oracle model. In this paper, we propose a novel bit-composition protocol with robustness independent of a statistical parameter by introducing additional clients generating the pair of shares of random values only in the offline phase (which can be performed without the parties' inputs). Our protocol is based on a maliciously secure four-party protocol with one corruption using replicated secret sharing. The security of our protocol is proved in the standard model (which is a weaker assumption than the random oracle model). Our protocol achieves efficiency and the strongest security simultaneously. We also propose a protocol for the Hamming distance with robustness by modifying our bit-composition protocol. It can achieve a secure iris recognition service via MPC with robustness. Furthermore, we extend our protocol with a constant number of parties and clients to one with an arbitrary number of parties and clients.
Secure multiparty computation (MPC) enables parties to compute an arbitrary function without revealing each party's inputs. A typical MPC is secret-sharing based MPC (SS-MPC). In the SS-MPC, each party distributes its inputs, and the computation proceeds with secret shares that look exactly like random numbers distributed among the parties. In the SS-MPC protocol, the parties can compute any function represented as a circuit by using shares locally and communicating among the parties. In particular, when the parties compute a complex function composed of binary and arithmetic circuits, an efficient share conversion protocol facilitates the computation of it. An important conversion protocol is a bit-composition protocol that converts a k-dimensional vector with shares on ℤ2 (i.e., shares of binary sequence) to shares on ℤ2k (i.e., shares of decimal value). Previous studies proposed a maliciously secure bit-composition protocol with robustness, which is a security notion that all parties learn the correct output regardless of the attacker's behaviour. However, its security is dependent on a statistical parameter or proved in the random oracle model. In this paper, we propose a novel bit-composition protocol with robustness independent of a statistical parameter by introducing additional clients generating the pair of shares of random values only in the offline phase (which can be performed without the parties' inputs). Our protocol is based on a maliciously secure four-party protocol with one corruption using replicated secret sharing. The security of our protocol is proved in the standard model (which is a weaker assumption than the random oracle model). Our protocol achieves efficiency and the strongest security simultaneously. We also propose a protocol for the Hamming distance with robustness by modifying our bit-composition protocol. It can achieve a secure iris recognition service via MPC with robustness. Furthermore, we extend our protocol with a constant number of parties and clients to one with an arbitrary number of parties and clients.
Secure multiparty computation (MPC) enables par-ties to compute an arbitrary function without revealing each party’s inputs. A typical MPC is the secret sharing based MPC (SS-MPC). In the SS-MPC, each party distributes its inputs, and the computation proceeds with secret shares that just look like random numbers distributed among the parties. In the SS-MPC protocol, the parties can compute any function represented as a circuit by using shares locally and communicating among the parties. In particular, when the parties compute a complex function composed of binary and arithmetic circuits, an efficient share conversion protocol facilitates the computation of it. An important conversion protocol is the bit-composition protocol that converts a k-dimensional vector with the shares on Z 2 (i.e., shares of binary sequence) to the shares on Z 2 k (i.e., shares of decimal value). The previous work proposed a maliciously secure bit-composition protocol with guaranteed output delivery (GOD), which is the security notion that all the parties learn the correct output regardless of the attacker’s behaviour. However, its security is proved in the random oracle model.In this paper, we propose a new bit-composition protocol with GOD by introducing additional clients just helping the parties during computation. Our protocol is based on a maliciously secure four-party protocol with one corruption using replicated secret sharing. The security of our protocol is proved in the standard model (which is weaker than the random oracle model). Our protocol achieves the efficiency and strongest security simultaneously. We also propose a protocol for the Hamming distance with GOD by modifying our bit-composition protocol. It achieves a secure iris recognition service via MPC with GOD.
parties to securely compute an agreed function f over some finite field in the presence of a computationally unbounded adversary, who can maliciously corrupt any t out of the n parties. Most of the known efficient MPC protocols are designed in the offline- online framework introduced in a seminal work by Beaver in CRYPTO 1991. In this framework, the parties generate shared random and private multiplication-triples during the offline phase, which are used later in the online phase for securely evaluating the multiplication gates in the circuit representing f . The efficiency of the MPC protocols in this framework then relies on efficient ways of implementing the offline phase. In this paper, we propose a new and simple framework for generating shared and private random multiplication triples with unconditional security. The existing protocols approach this problem by first producing shared pairs of private and random values, followed by securely computing the shared product of each pair of values. The latter task involves a multiplication protocol for shared values that are typically communication intensive. Our framework takes a completely different approach and shuns the use of multiplication protocol. Namely, we ask the parties to verifiably share random multiplication triples and then securely extract shared random multiplication triples unknown to the adversary, from the shared triples. Realizing our framework in the asynchronous and hybrid network setting,1 we present the first ever MPC protocols with a linear (in the number of parties) communication overhead per multiplication gate in the circuit representing f . These are significant improvements over the best known existing MPC protocols in the asynchronous and hybrid network setting with communication complexity O(n2) and O(n3), respectively. Our framework when applied to the synchronous setting results in round-efficient MPC protocols.
The N sets of parties which are allowed by unconditionally the secure multiparty computation (MPC) for computing securely with a registered function f with the help of unbounded adversary computational at some specified field. Here one can corrupt t among n parties maliciously corrupt. The Protocols of MPC which are known and efficient are developed for online or offline framework. Coming to the offline process, the private & random multiplication-triples which is sharable can be generated by the parties in this framework. Later on, these are useful for online to evaluate the multiplication of gates securely in a circuit which describes as f. In this, Protocols of the MPC efficiency depends on the how the offline implementation efficiently. Here, we proposed a simple method, for shared & private multiplication-triples which are random in nature generation without any conditions securely & safely. The typical protocols face this issue, when the random values of shared pairs produced initially. And also, in computing the product values which is shared for every pair. After that, protocols of multiplication and values which are considered as communication intensive. In proposed scheme, the multiplication protocols are completely used in different manner. Later on, we observe that the share multiplication-triples verification by parties or they are extracted securely or not. With the use of setting of the hybrid network and asynchronous, linear communication MPC protocols used which are multiplication gate overhead & indicates as f. The above are the improvements on the typical MPC protocols with the help of hybrid networking setting, asynchronous and complexity of the communication, if we give to result of synchronous setting in our system. It results efficient MPC protocols which are rounded.
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: 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. 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.
We construct a multiparty computation (MPC) protocol that is secure even if a malicious adversary, in addition to corrupting 1-ε fraction of all parties for an arbitrarily small constant ε >0, can leak information about the secret state of each honest party. This leakage can be continuous for an unbounded number of executions of the MPC protocol, computing different functions on the same or different set of inputs. We assume a (necessary) "leak-free" preprocessing stage. We emphasize that we achieve leakage resilience without weakening the security guarantee of classical MPC. Namely, an adversary who is given leakage on honest parties' states, is guaranteed to learn nothing beyond the input and output values of corrupted parties. This is in contrast with previous works on leakage in the multi-party protocol setting, which weaken the security notion, and only guarantee that a protocol which leaks l bits about the parties' secret states, yields at most l bits of leakage on the parties' private inputs. For some functions, such as voting, such leakage can be detrimental.
Secure Multiparty Computation (MPC) is an expression encompassing cryptographic techniques that allow mutually distrustful parties to jointly perform computations over private data, ensuring correctness and preserving privacy despite malicious behavior. Guaranteed output is the strongest security goal for MPC: protocols with this property always deliver results. This is in contrast with weaker notions that allow malicious aborts. The seminal works of Ben-Or, Goldwasser, and Wigderson (STOC’88) and Rabin and Ben-Or (STOC’89) showed interactive protocols to compute any function with guaranteed output and perfect security if fewer than one third of parties are corrupted, or with statistical security (with a small error probability) if fewer than half are corrupted. These results hold when the set of participants is fixed throughout the execution. Ostrovsky and Yung’s proactive model (PODC’91) relaxes this assumption by allowing the set of corrupted parties to evolve over time, better capturing the dynamics of long-lived computations, where machines may be periodically compromised and recovered. The recent YOSO (You Only Speak Once) and fluid MPC models (CRYPTO’21) push this ambitious modelling even further by allowing for fully dynamic participation, with parties joining and leaving the computation at will. In this setting, known protocols with guaranteed output fall short of optimal resilience or rely on non-standard communication and adversarial assumptions. Matching the classical BGW and Rabin–Ben-Or bounds in these settings remained an open problem. We resolve these questions within the Layered MPC abstraction of David et al. (CRYPTO’23), in which the interaction pattern of a protocol is restricted to be a layered graph, meaning parties are partitioned into a sequence of disjoint sets (layers) and can send private and broadcast messages to parties in immediately subsequent layers. We match the BGW and Rabin and Ben-Or bounds in this model, fully characterizing the feasibility landscape of Layered MPC with guaranteed output. As a stepping stone towards our statistically secure protocol, we construct a more efficient and conceptually simpler computationally secure protocol relying on linear non-interactive commitments. Our results yield optimally-resilient and maximally-proactive MPC protocols with guaranteed output for both perfect and statistical security.