Identifying critical nodes in multi-layered networks under multi-vector malware attack

Cuenda, Sara and Vida Delgado, Rafael Ángel and Galeano, Javier (2013). Identifying critical nodes in multi-layered networks under multi-vector malware attack. In: "Net-Works 2013 International Conference. Complex and Multiplex Networks: Structure, Applications and Related Topic", 11/12/2013-13/12/2103, El Escorial, Madrid. pp. 97-105.

Description

Title: Identifying critical nodes in multi-layered networks under multi-vector malware attack
Author/s:
  • Cuenda, Sara
  • Vida Delgado, Rafael Ángel
  • Galeano, Javier
Item Type: Presentation at Congress or Conference (Article)
Event Title: Net-Works 2013 International Conference. Complex and Multiplex Networks: Structure, Applications and Related Topic
Event Dates: 11/12/2013-13/12/2103
Event Location: El Escorial, Madrid
Title of Book: International Journal of Complex Systems in Science
Date: December 2013
ISSN: 2174-6036
Subjects:
Freetext Keywords: multi-layered networks; spreading models; MSC 2000: 05C82
Faculty: E.T.S. de Ingeniería Agronómica, Alimentaria y de Biosistemas (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Computer viruses are evolving by developing multiple spreading mechanisms that are simultaneously used during the infection process. The identification of the nodes that allow a better spreading efficiency of these kind of viruses is becoming a determinant part of the defensive strategy against malware. These multi-vector viruses can be modeled in multi-layered networks in which each node belongs simultaneously to different layers, adapting the spreading vector to the properties of the layer. This way, the same virus has different propagation rates in each layer and also in the multi-layered network considered as a whole. The set of nodes selected as initial group of infected subjects can determine the final propagation of the infection. In this work, we analyze the spreading of a virus in a multi-layered network formed by M layers, given different sets of initial infected nodes, and, in particular, the effect of the initial selection on the efficiency of the infection. The initial group of infected nodes is selected according to properties of the nodes considered as part of a layer and also of the whole system. As an example, we apply this study to a multi-layered network formed by two layers: the social network of collaboration of the Spanish scientific community

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainFIS2011-22449PRODIEVOUnspecifiedProcesos Dinámicos Evolutivos: virus, ecosistemas y comportamientos sociales
Government of SpainMTM2012-39101-C02-01CAOSRosa María Benito ZafrillaCaos clásico y cuántico en sistemas hamiltonianos y complejidad
Madrid Regional GovernmentS2009/ESP-1691MODELICOUnspecifiedModelización y simulación de sistemas complemos

More information

Item ID: 53633
DC Identifier: http://oa.upm.es/53633/
OAI Identifier: oai:oa.upm.es:53633
Official URL: http://www.ij-css.org/volume-03_01/ijcss03_01-097.pdf
Deposited by: Memoria Investigacion
Deposited on: 28 Mar 2019 13:14
Last Modified: 28 Mar 2019 13:14
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