Analyzing Malware Propagation on Wireless Sensor Networks: A New Approach Using Queueing Theory and HJ-Biplot with a SIRS Model

[EN]Most research on malware focuses mainly on its detection, without paying attention to its propagation trends. However, modeling the spread of malware is an important research problem because it allows us to predict how malware will evolve and to take steps to prevent its propagation, hence the i...

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Detalles Bibliográficos
Autores: Frutos Bernal, Elisa, Rodríguez Rosa, Miguel, Anciones Polo, María del Dulce Nombre, Martín del Rey, Ángel María
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Universidad de Salamanca (USAL)
Repositorio:GREDOS. Repositorio Institucional de la Universidad de Salamanca
OAI Identifier:oai:gredos.usal.es:10366/159962
Acceso en línea:http://hdl.handle.net/10366/159962
Access Level:acceso abierto
Palabra clave:Malware propagation
Closed queuing networks
HJ-Biplot
Individual-based models
Wireless sensor networks
SIRS models
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spelling Analyzing Malware Propagation on Wireless Sensor Networks: A New Approach Using Queueing Theory and HJ-Biplot with a SIRS ModelFrutos Bernal, ElisaRodríguez Rosa, MiguelAnciones Polo, María del Dulce NombreMartín del Rey, Ángel MaríaMalware propagationClosed queuing networksHJ-BiplotIndividual-based modelsWireless sensor networksSIRS models[EN]Most research on malware focuses mainly on its detection, without paying attention to its propagation trends. However, modeling the spread of malware is an important research problem because it allows us to predict how malware will evolve and to take steps to prevent its propagation, hence the interest in analyzing this spread from a statistical point of view. This work proposes a malware propagation prediction methodology based on multivariate statistical techniques such as HJ-Biplot in combination with closed queuing networks. Datasets generated using individual-based SIRS models are used to validate the proposed methodology, although any other model could have been chosen to test its validity. Experimental results show that the proposed model can effectively predict and classify malware and discover the influence of different model parameters on the malware propagation situation.MDPI202420242023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10366/159962reponame:GREDOS. Repositorio Institucional de la Universidad de Salamancainstname:Universidad de Salamanca (USAL)Inglésinfo:eu-repo/semantics/openAccessoai:gredos.usal.es:10366/1599622026-06-07T06:28:51Z
dc.title.none.fl_str_mv Analyzing Malware Propagation on Wireless Sensor Networks: A New Approach Using Queueing Theory and HJ-Biplot with a SIRS Model
title Analyzing Malware Propagation on Wireless Sensor Networks: A New Approach Using Queueing Theory and HJ-Biplot with a SIRS Model
spellingShingle Analyzing Malware Propagation on Wireless Sensor Networks: A New Approach Using Queueing Theory and HJ-Biplot with a SIRS Model
Frutos Bernal, Elisa
Malware propagation
Closed queuing networks
HJ-Biplot
Individual-based models
Wireless sensor networks
SIRS models
title_short Analyzing Malware Propagation on Wireless Sensor Networks: A New Approach Using Queueing Theory and HJ-Biplot with a SIRS Model
title_full Analyzing Malware Propagation on Wireless Sensor Networks: A New Approach Using Queueing Theory and HJ-Biplot with a SIRS Model
title_fullStr Analyzing Malware Propagation on Wireless Sensor Networks: A New Approach Using Queueing Theory and HJ-Biplot with a SIRS Model
title_full_unstemmed Analyzing Malware Propagation on Wireless Sensor Networks: A New Approach Using Queueing Theory and HJ-Biplot with a SIRS Model
title_sort Analyzing Malware Propagation on Wireless Sensor Networks: A New Approach Using Queueing Theory and HJ-Biplot with a SIRS Model
dc.creator.none.fl_str_mv Frutos Bernal, Elisa
Rodríguez Rosa, Miguel
Anciones Polo, María del Dulce Nombre
Martín del Rey, Ángel María
author Frutos Bernal, Elisa
author_facet Frutos Bernal, Elisa
Rodríguez Rosa, Miguel
Anciones Polo, María del Dulce Nombre
Martín del Rey, Ángel María
author_role author
author2 Rodríguez Rosa, Miguel
Anciones Polo, María del Dulce Nombre
Martín del Rey, Ángel María
author2_role author
author
author
dc.subject.none.fl_str_mv Malware propagation
Closed queuing networks
HJ-Biplot
Individual-based models
Wireless sensor networks
SIRS models
topic Malware propagation
Closed queuing networks
HJ-Biplot
Individual-based models
Wireless sensor networks
SIRS models
description [EN]Most research on malware focuses mainly on its detection, without paying attention to its propagation trends. However, modeling the spread of malware is an important research problem because it allows us to predict how malware will evolve and to take steps to prevent its propagation, hence the interest in analyzing this spread from a statistical point of view. This work proposes a malware propagation prediction methodology based on multivariate statistical techniques such as HJ-Biplot in combination with closed queuing networks. Datasets generated using individual-based SIRS models are used to validate the proposed methodology, although any other model could have been chosen to test its validity. Experimental results show that the proposed model can effectively predict and classify malware and discover the influence of different model parameters on the malware propagation situation.
publishDate 2023
dc.date.none.fl_str_mv 2023
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10366/159962
url http://hdl.handle.net/10366/159962
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:GREDOS. Repositorio Institucional de la Universidad de Salamanca
instname:Universidad de Salamanca (USAL)
instname_str Universidad de Salamanca (USAL)
reponame_str GREDOS. Repositorio Institucional de la Universidad de Salamanca
collection GREDOS. Repositorio Institucional de la Universidad de Salamanca
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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