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Journal of Guizhou University

Rational Fair Secure Multiparty Computation Based on Chinese Remainder Theorem

Liu Rong-fe

Published Jan 1, 2014• 0 citations
OpenAlex

Abstract

Exciting rational secure multiparty computation goes less to discuss asynchronous channel,we realize it on asynchronous channel by using Chinese reminder theorem. Using the way of uncertain rounds,rational players don't which round is the last round. Through tit for tat mechanism and dynamical add / remove,rational players have not any motivation to deviate from the specified protocol,if someone deviate from it,then his utility yields less than follow it,so we realize any number of players' fair rational secure multiparty computation. Furthermore,we analyze the scheme's fairness from the perspective of game theory. Finally,some advantages of our scheme are demonstrated further by comparing the exiting schemes with the type of communication channel,consists of players,interactive round and other requests.

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Exciting rational secure multiparty computation goes less to discuss asynchronous channel,we realize it on asynchronous channel by using Chinese reminder theorem. Using the way of uncertain rounds,rational players don't which round is the last round. Through tit for tat mechanism and dynamical add / remove,rational players have not any motivation to deviate from the specified protocol,if someone deviate from it,then his utility yields less than follow it,so we realize any number of players' fair rational secure multiparty computation. Furthermore,we analyze the scheme's fairness from the perspective of game theory. Finally,some advantages of our scheme are demonstrated further by comparing the exiting schemes with the type of communication channel,consists of players,interactive round and other requests.
In the problem of rational secret sharing, each player, who prefers to be the only one to learn the secret, acts rationally rather than merely honestly or maliciously in the traditional cryptographic settings. The core issue of rational secret sharing is to construct a mechanism so that all rational participants have incentive to provide their shares in the reconstruction phase. However, lack of enough incentive and how to achieve fairness in asynchronous model are always the hot potatoes for obtaining a deterministic protocol in this field. In this paper, we devote our attention to solving the above two difficulties in asynchronous model and succeed in obtaining a satisfactory result, 1/p-rational secret sharing protocol, in 2-out-of-2 case. Firstly, we apply the repeated interaction method to provide motivation so as to attract the players to participant in the collaboration and make it possible for a deterministic protocol. Secondly, inspired by 1/p-security of partial fairness, we propose a new concept, 1/p-advantage, to reduce the unavoidable probability of unfairness in asynchronous model to a satisfactory level. Besides, in order to perfect our protocol, we bring in the augmented perfect coin-tossing to determine the sending-order at the start of every round. Compared with previous ones, our protocol is applicable to the asynchronous model as well as the traditional synchronous model, which makes our protocol more practical. Furthermore, the new concept, 1/p-advantage, gives us a new perspective on rational secret sharing and makes our solution fresh.
The field of rational cryptography considers the design of cryptographic protocols in the presence of rational agents seeking to maximize local utility functions. This departs from the standard secure multiparty computation setting, where players are assumed to be either honest or malicious. We detail the construction of both a two-party and a multiparty game theoretic framework for constructing rational cryptographic protocols. Our framework specifies the utility function assumptions necessary to realize the privacy, correctness, and fairness guarantees for protocols. We demonstrate that our framework correctly models cryptographic protocols, such as rational secret sharing, where existing work considers equilibrium concepts that yield unreasonable equilibria. Similarly, we demonstrate that cryptography may be applied to the game theoretic domain, constructing an auction market not realizable in the original formulation. Additionally, we demonstrate that modeling players as rational agents allows us to design a protocol that destabilizes coalitions. Thus, we establish a mutual benefit from combining the two fields, while demonstrating the applicability of our framework to real-world market environments. We also give an application of game theory to adversarial interactions where cryptography is not necessary. Specifically, we consider adversarial machine learning, where the adversary is rational and reacts to the presence of a data miner. We give a general extension to classification algorithms that returns greater expected utility for the data miner than existing classification methods.
In the setting of ( , ) mn rational secret sharing, n rational players wish to share a secret s , arbitrarily m players can reconstruct it, they always choose the strategies which can bring them more utilities.The security requirement includes privacy, correctness and fairness.Fairness is a central objective of the rational secret sharing scheme, complete fair means either all players get the secret s or none of them get it, but most existing schemes do not meet this nature.In this work, a rational secret sharing protocol is proposed, which neither need particular communication channel, nor assume the existence of honest minority, in addition, the scheme can resist the collusion attack with () k k m  players, and can achieve sequential equilibrium.Theoretical analysis shows that the proposed protocol is complete fair.
Rational secure multi-party computation means two or more rational parties complete a function on private inputs. Unfortunately, players sending false information can prevent the protocol from executing correctly, which will destroy the fairness of the protocol. To ensure the fairness of the protocol, the existing works on achieving fairness by specific utility functions. In this paper, we leverage game theory to propose the direction entropy-based solution. To this end, we utilize the direction entropy to examine the player's strategy uncertainty and quantify its strategy from different dimensions. Then, we provide mutual information to construct a new utility for the players. What's more, we measure the mutual information of players to appraise their strategies. By analyzing and proofing of protocol, we show that the protocol reaches a Nash equilibrium when players choose a cooperative strategy. Furthermore, we solve the fairness of the protocol. Compared to the previous approaches, our protocol is not required deposits and design-specific utility functions.
ABSTRACT Rational secure two‐party computation (RSTPC) applies game theory to cryptographic protocols, where rational parties only care about how to maximize their utilities. Fairness can be achieved by assuming rational behavior in RSTPC. Previous RSTPC protocols achieve fairness under symmetric information, which seems quite strong and unnatural for rational parties. In this paper, we consider a general RSTPC protocol under asymmetric information where previous equilibriums are inadequate to guarantee fairness. Therefore, we propose a stronger equilibrium named computationally sequential equilibrium to guarantee fairness under asymmetric information. Furthermore, our protocol only requires small constant communication rounds. Copyright © 2014 John Wiley & Sons, Ltd.