An Inquiry into the Evolutionary Game among Tripartite Entities and Strategy Selection within the Framework of Personal Information Authorization

IF 3.7 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jie Tang, Zhiyi Peng, Wei Wei
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Abstract

Mobile applications (Apps) serve as vital conduits for information exchange in the mobile internet era, yet they also engender significant cybersecurity risks due to their real-time handling of vast quantities of data. This manuscript constructs a tripartite evolutionary game model, “users-App providers-government”, to illuminate a pragmatic pathway for orderly information circulation within the App marketplace and sustainable industry development. It then scrutinizes the evolutionary process and emergence conditions of their stabilizing equilibrium strategies and employs simulation analysis via MATLAB. The findings reveal that (1) there exists a high degree of coupling among the strategic selections of the three parties, wherein any alteration in one actor’s decision-making trajectory exerts an impact on the evolutionary course of the remaining two actors. (2) The initial strategies significantly influence the pace of evolutionary progression and its outcome. Broadly speaking, the higher the initial probabilities of users opting for information authorization, App providers adopting compliant data solicitation practices, and the government enforcing stringent oversight, the more facile the attainment of an evolutionarily optimal solution. (3) The strategic preferences of the triadic stakeholders are subject to a composite influence of respective costs, benefits, and losses. Of these, users’ perceived benefits serve as the impetus for their strategic decisions, while privacy concerns act as a deterrent. App providers’ strategy decisions are influenced by a number of important elements, including their corporate reputation and fines levied by the government. Costs associated with government regulations are the main barrier to the adoption of strict supervision practices. Drawing upon these analytical outcomes, we posit several feasible strategies.
个人信息授权框架下三方实体间的进化博弈与策略选择探究
移动应用程序(Apps)是移动互联网时代信息交流的重要渠道,但由于其对海量数据的实时处理,也带来了巨大的网络安全风险。本手稿构建了一个 "用户-应用提供商-政府 "三方演化博弈模型,为应用市场的有序信息流通和行业的可持续发展指明了一条务实之路。然后,通过 MATLAB 进行仿真分析,对其稳定均衡策略的演化过程和出现条件进行了研究。研究结果表明:(1)三方的战略选择之间存在高度耦合,其中一方决策轨迹的任何改变都会对其余两方的演化过程产生影响。(2) 初始战略极大地影响着演化进程的速度和结果。概括地说,用户选择信息授权、App 提供商采取合规的数据征集做法以及政府实施严格监督的初始概率越高,就越容易实现进化过程中的最优解。(3)三方利益相关者的战略偏好受到各自成本、收益和损失的综合影响。其中,用户感知到的利益是其战略决策的动力,而隐私问题则是一种阻碍因素。应用程序提供商的战略决策受到一系列重要因素的影响,包括企业声誉和政府罚款。与政府法规相关的成本是采用严格监管措施的主要障碍。根据这些分析结果,我们提出了几种可行的策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Big Data and Cognitive Computing
Big Data and Cognitive Computing Business, Management and Accounting-Management Information Systems
CiteScore
7.10
自引率
8.10%
发文量
128
审稿时长
11 weeks
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