2015
Karyotis, V.; Papavassiliou, S.
Macroscopic malware propagation dynamics for complex networks with churn Journal Article
In: IEEE Communications Letters, vol. 19, no. 4, pp. 577-580, 2015, ISSN: 10897798, (cited By 22).
Abstract | Links | BibTeX | Tags: Complex networks, Computer crime; Malware; Queueing networks; Time varying networks, Developed model; Dynamic nodes; Limited energies; Malware attacks; Malware propagation; Network reliability; Network robustness; Product forms
@article{Karyotis2015577,
title = {Macroscopic malware propagation dynamics for complex networks with churn},
author = {V. Karyotis and S. Papavassiliou},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84927730777&doi=10.1109%2fLCOMM.2015.2399925&partnerID=40&md5=70ea29f069651e438d8b63decdc8a8f6},
doi = {10.1109/LCOMM.2015.2399925},
issn = {10897798},
year = {2015},
date = {2015-01-01},
journal = {IEEE Communications Letters},
volume = {19},
number = {4},
pages = {577-580},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {In this letter, a queueing-based approach for modeling malware propagation in complex networks with churn (dynamic node variation) is introduced. The proposed methodology captures the dynamics of SIS-type malware, especially in time-varying networks, where nodes enter and leave due to their limited energy reserves, or as the outcome of malware attacks. We demonstrate the developed model in various complex networks, showing how it can be exploited for analytically quantifying network reliability and further used for increasing the robustness of the network against generic malware attacks. © 2015 IEEE.},
note = {cited By 22},
keywords = {Complex networks, Computer crime; Malware; Queueing networks; Time varying networks, Developed model; Dynamic nodes; Limited energies; Malware attacks; Malware propagation; Network reliability; Network robustness; Product forms},
pubstate = {published},
tppubtype = {article}
}
In this letter, a queueing-based approach for modeling malware propagation in complex networks with churn (dynamic node variation) is introduced. The proposed methodology captures the dynamics of SIS-type malware, especially in time-varying networks, where nodes enter and leave due to their limited energy reserves, or as the outcome of malware attacks. We demonstrate the developed model in various complex networks, showing how it can be exploited for analytically quantifying network reliability and further used for increasing the robustness of the network against generic malware attacks. © 2015 IEEE.