Study on the Evolutionary Game of Information Security Supervision in Smart Cities under Different Reward and Punishment Mechanisms

At present, the information security problems of smart city show a high incidence, and it is necessary to strengthen the information security supervision of smart city. In the process of supervision, there is a game relationship between local government and smart city enterprises. This paper firstly constructs the game matrices of local government and enterprises under the static and three dynamic reward and punishment mechanisms, then conducts numerical simulation with the help of MATLAB to arrive at the optimal reward and punishment mechanism through comparison, and finally explores the influence of the change of the upper limit value of each key variable on the directionality and sensitivity of the decision-making behavior of game subjects under the optimal mechanism. The result shows that initial value is one of the decisive factors influencing the choice of management strategy by enterprise. Dynamic reward and dynamic punishment mechanism is the best reward and punishment mechanism for information security supervision in smart cities. In case the upper limit value of key parameters is increased, a larger punishment has a strong influence on the positive strategy choice of the enterprise, and a reasonable adjustment of the reward policy can likewise mobilize the probability that the enterprise actively chooses to strengthen information security management. Based on the simulation results, we propose a feasible strategy.