Dynamics of Complex Networks: Malware Propagation Modeling and Analysis in Industrial Internet of Things

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Abstract

While cyber physics system (CPS) provides forward-looking and personalized services for users, it also creates conditions for the spread of malware. Therefore, it's critical for us to analyse affecting factors and study the propagation characteristics of malware. On the basis of the difference of intelligent device's dissemination capacity and discriminant ability, a dynamic malware propagation model (Disseminate&Discriminate-Spread-Exposed-Ignorant-Recover, DDSEIR) is proposed. First, intelligent devices are classified into different groups according to the level of dissemination capability by hierarchical mechanism, which takes the networks topology into account. And subsequently, intelligent device's discriminant ability can be evaluated by sender's identity and information attributes. Then, the mean field equation is constructed to analyze the dynamic characteristics of DDSEIR and the factors that influence malware propagation, which is used to further derive the malware propagation scale and threshold value of diffusion. Finally, this paper uses Live Journal dataset to verify the effectiveness of DDSEIR. The experiments illustrate that intelligent device's dissemination capacity and discriminant ability have significant influences on malware propagation.

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Li, L., Cui, J., Zhang, R., Xia, H., & Cheng, X. (2020). Dynamics of Complex Networks: Malware Propagation Modeling and Analysis in Industrial Internet of Things. IEEE Access, 8, 64184–64192. https://doi.org/10.1109/ACCESS.2020.2984668

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