Keywords
small world network
complex networks
time game
offensive and defensive confrontation
How to Cite
Abstract
In a complex network environment, this study introduces the susceptible sick removed model to solve the optimal defense action timing. By combining FlipIt game theory, a complex network attack and defense time game model is designed. The game equilibrium is solved and an algorithm for selecting the optimal defense time strategy is proposed. The data validate that the relationship between the sizes of PA and PD is different, corresponding to different defense effects. In a small world network with PA=5 and PD=3, the k value was 32. At 60 seconds, the proportion of I1 was 0.448, 0.280 higher than S1. In a network with PA=3 and PD=4, the proportion of infected nodes fluctuated between 0.670 and 0.850 as node proportion stabilized. Adjusting the time strategy dynamically significantly increased defense benefits. Compared to PD=4, a PD=6 defense strategy resulted in a 161.36% defense revenue increase. In the current complex network environment, the application of game theory can provide a foundation for methods of optimal defense timing decision-making. In the context of a complex Internet with small-world effects and scale-free characteristics in the real world, the research method has been demonstrated to effectively enhance network defense effectiveness by dynamically adjusting the time strategy.
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