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arXiv:2110.09160 · International Journal of Intelligent Systems

DE‐RSTC: A rational secure two‐party computation protocol based on direction entropy

Yuling Chen, Juan Ma, Xianmin Wang, Xinyu Zhang, Huiyu Zhou

Published Aug 16, 2022• 9 citations
arXivHTMLPDF

Abstract

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.

DOI
10.1002/int.22975

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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 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.
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.
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.
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.
Abstract Secure multi-party computation(SMPC) is an important research area in cryptography with many application scenarios, but there are still many problems to be solved. Aiming at security and fairness issues in SMPC, we consider that semi-honest participants are able to execute the protocol according to the specification, but there would be some additional malicious operations such as collusion and refuse to exchange information in the process of information interaction, which leads to deviations in the security and fairness of the protocol. To solve the above problems, we combine information entropy and mutual information to propose an n-round information exchange protocol, in which each participant broadcasts a relevant information value in each round without revealing additional information. The uncertainty of the correct result value is fuzzed by the interactive information in each round, and each participant cannot determine the correct result value until the end of the protocol, which effectively prevents malicious behavior and ensures the correct execution of the protocol. Security analysis and fairness analysis show that under the semi-honest model, our protocol guarantees the security and relative fairness of the output obtained by the participants after completing the protocol.
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.