基于议价贝叶斯博弈模型的防欺诈策略

doi:10.3969/j.issn.1671-1122.2021.04.009

信息网络安全 ›› 2021, Vol. 21 ›› Issue (4): 81-88.doi: 10.3969/j.issn.1671-1122.2021.04.009

基于议价贝叶斯博弈模型的防欺诈策略

任航¹, 程相国¹(), 张睿², 夏辉²

1.青岛大学计算机科学技术学院,青岛 266071
2.中国海洋大学信息科学与工程学院,青岛 266100

收稿日期:2021-01-16 出版日期:2021-04-10 发布日期:2021-05-14
通讯作者: 程相国 E-mail:15964252399@163.com
作者简介:任航（1997—）,女,山东,硕士研究生,主要研究方向为众包计算、网络安全|程相国（1969—）,男,山东,教授,博士,主要研究方向为密码学、信息安全|张睿（1995—）,女,山东,硕士研究生,主要研究方向为对抗攻击、网络安全|夏辉（1986—）,男,山东,教授,博士,主要研究方向为众包计算、对抗攻击、物联网安全。
基金资助:
国家自然科学基金(61872205);山东省自然科学基金(ZR2019MF018);青岛市应用基础研究计划(18-2-2-56-jch)

A Novel Fraud Prevention Strategy Based on Bargaining Bayesian Game Model

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

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

摘要/Abstract

摘要：

多媒体信息易遭受敌手攻击,如恶意应用通过虚假报价来欺诈未采取防护措施的用户,导致用户财产或隐私面临极大的威胁。为解决上述问题,文章提出一种基于议价贝叶斯博弈模型的防欺诈策略来保护用户隐私。首先利用四轮讨价还价确定应用和用户交互时的收益矩阵,引入常规用户的检测率对收益矩阵进行调整,抑制恶意应用虚假报价;然后通过贝叶斯纳什均衡分析确定用户的最优防御策略以防止用户遭受恶意应用的欺骗,避免个人隐私泄露。仿真结果表明,文章方案提高了应用和用户在交易达成时各自的收益,降低了恶意应用采取欺骗策略的概率,增强了用户隐私的安全性。

关键词: 贝叶斯模型, 博弈论, 议价, 隐私保护

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

中图分类号:

TP309

任航, 程相国, 张睿, 夏辉. 基于议价贝叶斯博弈模型的防欺诈策略[J]. 信息网络安全, 2021, 21(4): 81-88.

REN Hang, CHENG Xiangguo, ZHANG Rui, XIA Hui. A Novel Fraud Prevention Strategy Based on Bargaining Bayesian Game Model[J]. Netinfo Security, 2021, 21(4): 81-88.

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恶意应用常规用户	N	Y
T	$(\eta -1)C_{\beta }^{T}$,0	$\eta (I_{\beta }-C_{\beta }^{T})$,$\eta (I_{\alpha }-I_{\beta })$
F	$-\eta (C_{\beta }^{F}\text{+}P_{e})$,$\eta P_{e}$	$(1-\eta )(I_{\beta }\text{+}P_{e}-C_{\beta }^{F})$,$(\eta -1)(I_{\beta }+P_{e})$

基于议价贝叶斯博弈模型的防欺诈策略

A Novel Fraud Prevention Strategy Based on Bargaining Bayesian Game Model

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