Abstract
The widespread use of online game accelerators also induces them to become a medium for hackers to spread Trojan horses. In this paper, we propose a novel compartment model which considered the heterogeneity of online computer game players aiming to characterize the Trojan propagation. Specifically, we distinguish rational game players from impulsive game players in our model. The spreading threshold is obtained, and the global stability of equilibrium is also verified. Moreover, Trojan’s control problem is studied by using Pontryagin’s maximum principle. Numerical results confirm the stability of the system and the effectiveness of the optimal control strategy. Besides, more numerical results also show that some control strategies such as warning and caution should be taken at the very beginning of game player downloading the malicious accelerator.
Highlights
Online game accelerator, as a computer program, is used to speed up online computer games
In the area of epidemic disease, establishing a dynamical model is recognized as an effective method to predict the scale of disease outbreaks and develop the constant control measures
Due to the difficulty of obtaining the real datasets, we develop simulation methods to verify theoretical results. is work consists of two parts: the first part is the simulations about dynamics of the SEIR model, and the second part is the simulations of the optimal control strategy
Summary
As a computer program, is used to speed up online computer games. Us, it is easy for attackers to spread Trojan via online game accelerators. Erefore, in this paper, we propose an SEIR (SusceptibleExposed-Infected-Recovered) model to address the problem of Trojan propagation via online game accelerators. We construct a state diagram for Trojan propagation via online game accelerators. En, some of exposed nodes enter the I-state compartment with the rate of ξa because impulsive players use the malicious online game b. According to the Routh–Hurwitz criterion [25], the disease-free equilibrium P0 of the system is locally asymptotically stable. If R0 ≤ 1, the disease-free equilibrium P0 of the system is globally asymptotically stable and unstable if R0 > 1. By LaSalle’s invariance principle [26], P∗ is globally asymptotically stable when R0 > 1. □
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