A Regulatory Game Analysis of Smart Aging Platforms Considering Privacy Protection

Int J Environ Res Public Health. 2022 May 9;19(9):5778. doi: 10.3390/ijerph19095778.

Abstract

Privacy and information protection are important issues in the era of big data. At present, China's elderly care industry is gradually adopting the supply model of smart elderly care to alleviate the contradiction between supply and demand. However, the low level of regulation of smart aging platforms may lead to a low level of privacy protection on the platforms. Therefore, in this paper, based on the evolutionary game and Lyapunov theory, we discuss the willingness of elderly people to participate in regulation, the privacy protection status of platform service providers, and the degree of government regulation, as well as the key factors affecting the equilibrium of the three-party game system, and conduct simulation analysis and game system optimization using MATLAB. The simulation results show that A1(0,0,1) and A5(0,0,0) can be transformed to A8(1,1,0) by adjusting the parameters, i.e., the optimal ESS is participation, high-quality protection, and low investment supervision; the service income of the elderly, the loss of privacy leakage, the investment cost of service providers, and the amount of government rewards and punishments are the key factors affecting the tripartite game system. By analyzing the impact of factors, such as benefits and costs, on privacy protection and the regulation of smart senior care platforms, the level of privacy protection of smart senior care platforms can be improved and the process of the comprehensive regulation of domestic senior care services can be promoted.

Keywords: evolutionary game; privacy disclosure; secret protection; smart aging platforms; supervisory.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aging
  • Big Data
  • Computer Security*
  • Government
  • Humans
  • Privacy*

Grants and funding

This research was funded by the Zhejiang Natural Science Foundation Projects (No. LQ20G010005) and the Zhejiang Provincial Statistical Science Research Project (NO. 21TJQN15).