IEEE Access (Jan 2024)

Evolutionary Game Research on the Data Security Supervision of the Internet of Vehicles

  • Miaocheng Yang,
  • Kai Zou,
  • Yihang Guo,
  • Xin Wei

DOI
https://doi.org/10.1109/ACCESS.2024.3471079
Journal volume & issue
Vol. 12
pp. 174668 – 174688

Abstract

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With the acceleration of the transformation of automobile intelligence and network connection, the data security of the Internet of Vehicles is confronted by continuous problems, thus becoming one of the hot issues of widespread concern in the society. Therefore, it is of great importance to strengthen the supervision of data security of the IOV. Based on this, this paper first constructs an evolutionary game model between government departments and the IOV enterprises under the static reward and punishment mechanisms and three different dynamic reward and punishment mechanisms. Secondly, it focuses on the evolutionary stability of the strategies of both parties in the four situations, and discusses the influences of the regulatory cost, reward intensity and punishment intensity on the strategic choices of both parties in the game. Finally, Matlab 2021b software is used to simulate the influence of four different reward and punishment mechanisms on the evolutionary stability strategy (ESS) and its evolution trend, and the influence of the variation of key parameters on the behavioral evolution of game players is discussed. The research results are as follows: (1) There is no ESS in the game system under the static reward and punishment mechanisms, and the introduction of the dynamic reward and punishment mechanisms can effectively make up for the shortcomings of the static reward and punishment mechanisms, so as to achieve evolutionarily stable equilibrium (ESE). (2) Since the dynamic reward and static punishment mechanisms (DRSPM) is superior to other dynamic reward and punishment mechanisms about the data security supervision of the IOV, it is the optimal reward and punishment mechanisms. (3) The probability of strengthening data security management of connected vehicle enterprises is negatively correlated with the intensity of incentives and supervision costs, and positively correlated with the intensity of penalties. According to the numerical simulation results, some feasible strategies for government departments to improve the data security supervision mechanism of the IOV have been proposed.

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