Heterogeneous Projection of Disruptive Malware Prevalence in Mobile Social Networks

Aldiyar Dabarov; Madiyar Sharipov; Aresh Dadlani; Muthukrishnan Senthil Kumar; Walid Saad; Choong Seon Hong

doi:10.1109/LCOMM.2020.2992562

Heterogeneous Projection of Disruptive Malware Prevalence in Mobile Social Networks

Aldiyar Dabarov, Madiyar Sharipov, Aresh Dadlani, Muthukrishnan Senthil Kumar, Walid Saad, Choong Seon Hong

Nazarbayev University

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

Segregating the latency phase from the actual disruptive phase of certain mobile malware grades offers more opportunities to effectively mitigate the viral spread in its early stages. Inspired by epidemiology, in this letter, a stochastic propagation model that accounts for infection latency of disruptive malware in both personal and spatial social links between constituent mobile network user pairs is proposed. To elucidate the true impact of unique user attributes on the virulence of the proposed spreading process, heterogeneity in transition rates is also considered in an approximated mean-field epidemic network model. Furthermore, derivations for the system equilibrium and stability analysis are provided. Simulation results showcase the viability of our model in contrasting between latent and disruptive infection stages with respect to a homogeneous population-level benchmark model.

Original language	English
Article number	9086444
Pages (from-to)	1673-1677
Number of pages	5
Journal	IEEE Communications Letters
Volume	24
Issue number	8
DOIs	https://doi.org/10.1109/LCOMM.2020.2992562
Publication status	Published - Aug 2020

Funding

Manuscript received February 8, 2020; revised March 23, 2020; accepted May 1, 2020. Date of publication May 6, 2020; date of current version August 12, 2020. This research was supported by the Faculty Development Competitive Research Grant (No. 240919FD3918), Nazarbayev University. The associate editor coordinating the review of this letter and approving it for publication was T. Han. (Corresponding author: Aresh Dadlani.) Aldiyar Dabarov, Madiyar Sharipov, and Aresh Dadlani are with the Department of ECE, Nazarbayev University, Nur-Sultan 010000, Kazakhstan (e-mail: [email protected]; [email protected]; [email protected]).

Keywords

disruptive virus
equilibrium analysis
heterogeneous epidemic model
mean-field theory
Mobile social networks

ASJC Scopus subject areas

Modelling and Simulation
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/LCOMM.2020.2992562

Cite this

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title = "Heterogeneous Projection of Disruptive Malware Prevalence in Mobile Social Networks",

abstract = "Segregating the latency phase from the actual disruptive phase of certain mobile malware grades offers more opportunities to effectively mitigate the viral spread in its early stages. Inspired by epidemiology, in this letter, a stochastic propagation model that accounts for infection latency of disruptive malware in both personal and spatial social links between constituent mobile network user pairs is proposed. To elucidate the true impact of unique user attributes on the virulence of the proposed spreading process, heterogeneity in transition rates is also considered in an approximated mean-field epidemic network model. Furthermore, derivations for the system equilibrium and stability analysis are provided. Simulation results showcase the viability of our model in contrasting between latent and disruptive infection stages with respect to a homogeneous population-level benchmark model. ",

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Heterogeneous Projection of Disruptive Malware Prevalence in Mobile Social Networks

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