دانلود رایگان مقاله مدلی برای انتشار بدافزار در شبکه های قابل گسترش بر اساس شایعه روند گسترش

Abstract

In this paper, we propose a dynamic model of malware propagation in scale-free networks (SFNs) based on a rumor spreading model. The proposed model, which is called the susceptible–exposed–infectious–recovered–susceptible with a vaccination state (SEIRS-V) model, illustrates the dynamics of malware propagation with respect to time in SFNs. The model considers the impact of software diversity to halt the outbreak of malware in networks. Using the SEIRS-V model, we derive the basic reproductive ratio that governs whether or not a malware is extinct. Furthermore, we calculate the number of diverse software packages installed on computer nodes that can be introduced as a parameter to prevent malware spreading. We accomplish the systematic analysis of the model and represent the local and global stability of malware-free equilibrium. Using numerical simulations, we examine the theoretical analysis. The effects of diversification and vaccination on the model are investigated. Simulation results demonstrate that the model is more effective than other existing models of malware propagation, in terms of reducing the density of infected node.

6. Conclusions

In this paper, we proposed a malware propagation model based on a rumor spreading model to study the dynamics of malware spreading in scale-free networks (SFNs). The proposed model considers the assignment of diverse software packages to network nodes to prevent malware propagation. We have used the susceptible–exposed–infectious–recovered–susceptible with a vaccination state (SEIRS-V) and analyzed the conditions for the stability of the malware-free equilibrium. We obtained the basic reproductive ratio (i.e., R0), and determined that the dynamics of the model is completely governed by R0. Furthermore, we derived the critical number of software packages based on R0 to guarantee that a malware infection does not become an epidemic in SFNs. As the number of distinct software packages (i.e., C) augments gradually, the value of R0 declines. Theoretical analysis presents that basic reproductive ratio is appreciably dependent on diversification and the network topology. We have also conducted a series of numerical simulations to confirm the correctness of the analytical results. We have compared the proposed model with existing ones and showed that our model provides a noticeable decrease in the infected nodes compared with other models (i.e., SIRS and SEIRS models), and also a decrease in the spreading speed. Moreover, the simulation results represented that the malware propagation is governed by the number of diverse software packages and the vaccinated rate. This can be used as a guideline to control malware propagation process and devise defense strategies. In the future, we will focus on investigating more complex malware propagation model to control malware spreading in SFNs. We will also extend the study of software diversity through automatic program transformation techniques for the assignment of diverse software packages to network nodes.