Netinfo Security ›› 2021, Vol. 21 ›› Issue (4): 81-88.doi: 10.3969/j.issn.1671-1122.2021.04.009

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A Novel Fraud Prevention Strategy Based on Bargaining Bayesian Game Model

REN Hang1, CHENG Xiangguo1(), ZHANG Rui2, XIA Hui2   

  1. 1. College of Computer Science and Technology, Qingdao University, Qingdao 266071, China
    2. College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China
  • Received:2021-01-16 Online:2021-04-10 Published:2021-05-14
  • Contact: CHENG Xiangguo E-mail:15964252399@163.com

Abstract:

The multimedia information is vulnerable to attacks by attackers. For example, malicious applications offer false quotes to fraud users who have not taken protective measures, resulting in great threats to users’ property or privacy. To solve the above problem, this paper proposed a novel fraud prevention strategy based on bargaining Bayesian game model to protect user privacy. To suppress the malicious application of false offer through bargaining, this scheme firstly used four rounds of bargaining to determine the income matrix, and introduced the detection rate adjustment of user to adjust it. To avoid personal privacy disclosure, this paper determined the optimal defense strategy by Bayesian Nash equilibrium analysis to prevent users from being deceived by malicious attackers. The simulation experiment results show that this strategy is able to increase the revenue of transactions between users and applications and reduce the probability of malicious applications adopting malicious deception strategies, thereby enhancing the security of user’s privacy.

Key words: Bayesian model, game theory, bargain, privacy protection

CLC Number: