社交网络平台隐私保护多阶段微分博弈决策模型研究  

Research on multi-stage differential game decision-making model of privacy protection on social network platform

作　　者：杨斯博[1] 褚晓璇 李青青 冯楠[1,2] YANG Sibo;CHU Xiaoxuan;LI Qingqing;FENG Nan(College of Management and Economics,Tianjin University,Tianjin 300072,China;Laboratory of Computation and Analytics of Complex Management Systems(CACMS),Tianjin University,Tianjin 300072,China)

机构地区：[1]天津大学管理与经济学部,天津300072 [2]天津大学复杂管理系统实验室,天津300072

出　　处：《管理工程学报》2025年第3期210-224,共15页Journal of Industrial Engineering and Engineering Management

基　　金：国家自然科学基金项目(72231004,71871155);天津市重点研发计划科技支撑重点项目(20YFZCSN01010)。

摘　　要：随着数字经济时代的到来,社交网络平台的数据隐私保护问题越来越受到人们的重视。考虑到政府监管因素,本文构建了一种基于收益最大化,着眼于社交网络平台和用户双方参与的隐私保护多阶段微分博弈决策模型,其以社交网络平台不同阶段的发展状况为线索,协调平台数据隐私保护的投入和用户隐私共享的努力程度,剖析了双方在独立决策的非合作博弈、平台激励的Stackelberg主从博弈、一致决策的合作博弈等不同阶段下平台与用户之间最优的数据隐私保护策略。本文最后通过数值仿真实验对理论模型进行了验证,探讨了参数变化对最优策略及最优收益的影响,并给出相关管理启示。研究结果表明:社交网络平台对用户的成本分担虽不能提高其隐私保护水平,但能有效提升用户共享隐私信息的意愿,且在政府监管的情况下,相较其他博弈模式,一致决策的合作博弈可以显著提高双方的整体收益,实现社会效益的最大化。With the rapid development of the Internet and information technology,China′s digital economy is developing rapidly and has become a new driving force for China′s economic growth.As a mainstream platform for communication in the digital economy,the usefulness and attractiveness of social networking platforms derive from the sharing of data among users.The continuous increase in the number of platforms′users has brought a large amount of data resources.The continuous upgrading of platforms′services makes the data information generated by users have strong interest attributes,and it is easy to become the target of hackers or competitors.This has led to frequent leakage of private information,continuous negative news on social network platforms,and increasingly prominent personal privacy and security issues of users.Social network data privacy protection issues have received more and more attention.The current research on social network privacy protection mainly focuses on the willingness and choice,influencing factors and mechanisms of the privacy protection behavior of both platforms and users through empirical and evolutionary game methods.There are few studies on platform and user privacy protection decision in social network environment.Moreover,in the actual social network environment,the privacy protection level of the system is not static.Therefore,this article uses differential game theory as an approach to study the multi-stage decision-making problem of privacy protection between platforms and users in social networks from a dynamic perspective,including how both parties achieve a balance between benefits and costs,and how different factors affect the overall and individual benefits of the platform and users,which makes the research closer to reality and provides a theoretical basis for social network platforms and users to formulate privacy protection policies.In the first part,we start from the perspective of privacy protection decisions and government regulation between social network platforms

关 键 词：社交网络平台 隐私保护 多阶段决策模型 微分博弈 最优策略 

分 类 号：F224.32[经济管理—国民经济]