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Concurrency and Computation Practice and Experience

Social rational secure multi‐party computation

Yilei Wang, Zhe Liu, Hao Wang, Qiuliang Xu

Published Jul 1, 2013• 16 citations
Publisher

Abstract

SUMMARY Rational party is a new kind of parties who behave neither like honest parties nor like malicious adversaries. The crux point of rational party is the definition of the utility function, as rational parties only care about how to maximize their utility. In other words, rational parties choose the strategies, which can bring them the highest utilities. In rational secure two‐party computation protocol, the main task is how to boost mutual cooperation to complete the protocol. Social rational secure multi‐party computation (SRSMPC) means that in a social network, some distributed and rational parties with reputation properties want to jointly compute a functionality. The seemingly simple task becomes tough under three conditions. The first condition is that the network composed by parties may not be complete. That is, two parties may not be neighbors and they are connected through other parties. The second is that the network may be not secure. That is, messages may be tempered by malicious parties. The third condition is that parties may run the protocol under incomplete information scenario. That is, parties may have types and each type has a corresponding utility function. Under the first and second conditions, parties need to consider how to securely transmit messages between two parties who are not neighbors. Under the third condition, we propose the Tit‐for‐Tat strategy and prove that mutual cooperation is a sequential equilibrium between two parties. In this paper, we construct an SRSMPC protocol by using mechanism design under incomplete information to facilitate the implementation of the SRSMPC protocol within constant rounds. Meanwhile, newcomers are allowed to participate in the protocol. To the best of our knowledge, this is the first social rational secure computation protocol for multi‐party under an incomplete information scenario and an incomplete network. Copyright © 2013 John Wiley & Sons, Ltd.

DOI
10.1002/cpe.3057

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SUMMARY Rational party is a new kind of parties who behave neither like honest parties nor like malicious adversaries. The crux point of rational party is the definition of the utility function, as rational parties only care about how to maximize their utility. In other words, rational parties choose the strategies, which can bring them the highest utilities. In rational secure two‐party computation protocol, the main task is how to boost mutual cooperation to complete the protocol. Social rational secure multi‐party computation (SRSMPC) means that in a social network, some distributed and rational parties with reputation properties want to jointly compute a functionality. The seemingly simple task becomes tough under three conditions. The first condition is that the network composed by parties may not be complete. That is, two parties may not be neighbors and they are connected through other parties. The second is that the network may be not secure. That is, messages may be tempered by malicious parties. The third condition is that parties may run the protocol under incomplete information scenario. That is, parties may have types and each type has a corresponding utility function. Under the first and second conditions, parties need to consider how to securely transmit messages between two parties who are not neighbors. Under the third condition, we propose the Tit‐for‐Tat strategy and prove that mutual cooperation is a sequential equilibrium between two parties. In this paper, we construct an SRSMPC protocol by using mechanism design under incomplete information to facilitate the implementation of the SRSMPC protocol within constant rounds. Meanwhile, newcomers are allowed to participate in the protocol. To the best of our knowledge, this is the first social rational secure computation protocol for multi‐party under an incomplete information scenario and an incomplete network. Copyright © 2013 John Wiley & Sons, Ltd.
In traditional rational multi-party computation, parties are assumed to have utility functions and they act according to the utility assumptions. In economics and political scenarios, parties in multi-party computation may have some other properties such as reputation which plays an important role on boosting mutual cooperation in multiparty computation. In this paper we put forward a new kind of parties satisfying reputation assumption and utility assumptions. Meanwhile we construct a social rational multiparty computation protocol under incomplete information and incomplete network to facilitate the implementation of the protocol within constant rounds.
Abstract Fairness in secure two‐party computation ensures that either both of the communicating parties learn the output of some pre‐defined function or none of them does. Rational two‐party computation is an extension of two‐party computation that incorporates game theory into conventional two‐party (cryptographic) computation protocols for achieving fairness. From the standpoint of game theory, the strategies are designed for achieving equilibrium resulting in attaining fairness in rational two‐party computation protocols. Groce and Katz (Eurocrypt 2012) achieved fairness by computational Nash equilibrium under complete information. In this paper, protocols are considered in more practical scenarios of incomplete information, where fairness is achieved by sequential equilibrium. Our protocol has constant number of rounds as Groce and Katz do while achieving a stronger sequential equilibrium which also implies the computational Nash equilibrium. Copyright © 2015 John Wiley & Sons, Ltd.
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.
With the rapid development of mobile devices and wireless technologies, mobile social networks become increasingly available. People can implement many applications on the basis of mobile social networks. Secure computation, like exchanging information and file sharing, is one of such applications. Fairness in secure computation, which means that either all parties implement the application or none of them does, is deemed as an impossible task in traditional secure computation without mobile social networks. Here we regard the applications in mobile social networks as specific functions and stress on the achievement of fairness on these functions within mobile social networks in the presence of two rational parties. Rational parties value their utilities when they participate in secure computation protocol in mobile social networks. Therefore, we introduce reputation derived from mobile social networks into the utility definition such that rational parties have incentives to implement the applications for a higher utility. To the best of our knowledge, the protocol is the first fair secure computation in mobile social networks. Furthermore, it finishes within constant rounds and allows both parties to know the terminal round.
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.
Reputation is commonly used in game theory for mutual cooperation. Assuming that parties value their reputation as well as their payoffs just like people in the real world, this paper considers reputation assumptions when defining the utilities. The new utility consists of two parts: the reputation part and payoff part. The parties are redefined according to the new utility definition. Besides, to represent a more realistic adversary model, a new adversary named semi-rational party is proposed. The semi-rational parties behave like the combination of rational and covert parties. At last, a rational two-party secure computation protocol is constructed. The proof of fairness in the presence of the semi-rational party is stressed in this paper.