Social rational secure multi‐party computation

Abstract

SUMMARYRational 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.

Achieving fairness by sequential equilibrium in rational two‐party computation under incomplete information

“…Our protocol has finite iterations, and parties know the last iteration when the protocol terminates. In , we have the following result. Lemma Given m * =1 + (2 a − 4 c + 2 γ )/ γ , where m * denotes the remain iterations in the second stage of the protocol, there exists a sequential equilibrium such that both parties cooperate before t * = n − m * iterations, where n denotes the total iterations of the second stage.…”

“…Note that Lemma shows that rational parties have incentives to cooperate with others if we choose proper parameter m * , which has the same function as i * in . A detailed proof of Lemma can be found in Section 3.1 . Parameter m * is determined by the prior probability γ , which is a small probability that a party is a TFTer, while i * is determined by p , which is a parameter for geometric distribution.…”

A brief survey on secure multi-party computing in the presence of rational parties

“…Yilei Wang et al constructed a socio-rational secure multi-party computing protocol based on the socio-rational secret sharing scheme (Wang et al 2014). The basic idea is as follows: rational parities hope to complete the computation of a function through cooperation in a social network.…”

File sharing in cloud computing using win stay lose shift strategy

“…Furthermore, they prove that Nash equilibrium exists in several games and find the loss of efficiency due to selfish behavior is inevitable even though TFT is considered as a panacea to prevent selfish behaviors. Game theory can also be used in secret sharing schemes, where rational parties only want to maximize their utilities Halpern and Teague (2004);Wang et al (2014Wang et al ( , 2013.…”