Tripartite Evolutionary Game of Multiparty Collaborative Supervision of Personal Information Security in App: Empirical Evidence From China
At present, the problem of the personal information security of apps has attracted widespread attention from the government and society, and there is an urgent need for multiple subjects to participate in the regulation together. Based on this, we first considered the information feedback from users...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9856656/ |
| _version_ | 1817999857813553152 |
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| author | Yihang Guo Kai Zou Miaocheng Yang Chang Liu |
| author_facet | Yihang Guo Kai Zou Miaocheng Yang Chang Liu |
| author_sort | Yihang Guo |
| collection | DOAJ |
| description | At present, the problem of the personal information security of apps has attracted widespread attention from the government and society, and there is an urgent need for multiple subjects to participate in the regulation together. Based on this, we first considered the information feedback from users. Secondly, we constructed an evolutionary game model of three-party collaborative supervision among local governments, app distribution platforms, and users. Then the stability of the equilibrium points and their stability conditions are analyzed based on Lyapunov’s first law. Finally, MatlabR2021a software is used to analyze the influence of key parameter changes on the strategy choice of game players. The conclusions are as follows: (1) Increasing the penalty amount for local governments and app distribution platforms, increasing the reputation value premium or reputation loss from users’ feedback, and increasing synergistic benefits can promote local governments to adopt the strategies of supervision and app distribution platforms to adopt the strategies of review. (2) Reducing the cost of supervision for local governments can promote their adoption of supervisory strategies, and reducing the cost of review for app distribution platforms can promote their adoption of review strategies. (3) Reducing users’ feedback cost not only improves users’ enthusiasm to participate in supervision, but also promotes local governments and app distribution platforms to adopt positive strategies. (4) When the coefficient of synergistic benefit distribution is more even, it is more favorable for local governments and app distribution platforms to adopt positive strategies. Based on the simulation results, we propose some feasible strategies. |
| first_indexed | 2024-04-14T03:14:42Z |
| format | Article |
| id | doaj.art-537c6b8727444267b93ab1e65965a4db |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-14T03:14:42Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-537c6b8727444267b93ab1e65965a4db2022-12-22T02:15:30ZengIEEEIEEE Access2169-35362022-01-0110854298544110.1109/ACCESS.2022.31987059856656Tripartite Evolutionary Game of Multiparty Collaborative Supervision of Personal Information Security in App: Empirical Evidence From ChinaYihang Guo0https://orcid.org/0000-0002-3271-0459Kai Zou1Miaocheng Yang2https://orcid.org/0000-0001-6838-1653Chang Liu3School of Public Administration, Xiangtan University, Xiangtan, ChinaSchool of Public Administration, Xiangtan University, Xiangtan, ChinaSchool of Public Administration, Xiangtan University, Xiangtan, ChinaSchool of Public Administration, Xiangtan University, Xiangtan, ChinaAt present, the problem of the personal information security of apps has attracted widespread attention from the government and society, and there is an urgent need for multiple subjects to participate in the regulation together. Based on this, we first considered the information feedback from users. Secondly, we constructed an evolutionary game model of three-party collaborative supervision among local governments, app distribution platforms, and users. Then the stability of the equilibrium points and their stability conditions are analyzed based on Lyapunov’s first law. Finally, MatlabR2021a software is used to analyze the influence of key parameter changes on the strategy choice of game players. The conclusions are as follows: (1) Increasing the penalty amount for local governments and app distribution platforms, increasing the reputation value premium or reputation loss from users’ feedback, and increasing synergistic benefits can promote local governments to adopt the strategies of supervision and app distribution platforms to adopt the strategies of review. (2) Reducing the cost of supervision for local governments can promote their adoption of supervisory strategies, and reducing the cost of review for app distribution platforms can promote their adoption of review strategies. (3) Reducing users’ feedback cost not only improves users’ enthusiasm to participate in supervision, but also promotes local governments and app distribution platforms to adopt positive strategies. (4) When the coefficient of synergistic benefit distribution is more even, it is more favorable for local governments and app distribution platforms to adopt positive strategies. Based on the simulation results, we propose some feasible strategies.https://ieeexplore.ieee.org/document/9856656/Apppersonal information securitymulti-party collaborative supervisionusers’ feedbackevolutionary game |
| spellingShingle | Yihang Guo Kai Zou Miaocheng Yang Chang Liu Tripartite Evolutionary Game of Multiparty Collaborative Supervision of Personal Information Security in App: Empirical Evidence From China IEEE Access App personal information security multi-party collaborative supervision users’ feedback evolutionary game |
| title | Tripartite Evolutionary Game of Multiparty Collaborative Supervision of Personal Information Security in App: Empirical Evidence From China |
| title_full | Tripartite Evolutionary Game of Multiparty Collaborative Supervision of Personal Information Security in App: Empirical Evidence From China |
| title_fullStr | Tripartite Evolutionary Game of Multiparty Collaborative Supervision of Personal Information Security in App: Empirical Evidence From China |
| title_full_unstemmed | Tripartite Evolutionary Game of Multiparty Collaborative Supervision of Personal Information Security in App: Empirical Evidence From China |
| title_short | Tripartite Evolutionary Game of Multiparty Collaborative Supervision of Personal Information Security in App: Empirical Evidence From China |
| title_sort | tripartite evolutionary game of multiparty collaborative supervision of personal information security in app empirical evidence from china |
| topic | App personal information security multi-party collaborative supervision users’ feedback evolutionary game |
| url | https://ieeexplore.ieee.org/document/9856656/ |
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