Artificial neural network based detection of energy exhaustion attacks in wireless sensor networks capable of energy harvesting

dc.contributor.affiliationDepartamento de Comunicaciones
dc.contributor.affiliationEscuela Politécnica Superior de Gandia
dc.contributor.authorAlrajeh, Nabil Alies_ES
dc.contributor.authorKhan, Shafiullahes_ES
dc.contributor.authorLloret, Jaime
dc.contributor.authorLoo, Jonathanes_ES
dc.contributor.funderKing Saud University, Arabia Saudí
dc.date.accessioned2015-06-01T15:01:52Z
dc.date.issued2014
dc.description.abstract[EN] Energy consumption is the important factor when designing any mechanism for wireless sensor network (WSN). Research community is trying to enable energy harvesting mechanisms to provide long term energy source to WSN. However, energy consumption is generally greater than energy harvesting in WSN. Furthermore, if nodes are under any kind of energy exhaustion security attack, then energy harvesting mechanism cannot extend the lifetime of the WSN. In this paper, we propose a detection mechanism of energy exhaustion attacks that uses an artificial neural network (ANN). It has been developed for cluster-based WSN and takes into account the energy harvesting system. Simulation results show that our mechanism can detect and prevent such kind of attacks, even having lower percentage of false positives than other systems, and thus enlarge the wireless sensor node lifetime.en_EN
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationAlrajeh, NA.; Khan, S.; Lloret, J.; Loo, J. (2014). Artificial neural network based detection of energy exhaustion attacks in wireless sensor networks capable of energy harvesting. Adhoc and Sensor Wireless Networks. 22(1-2):109-133. https://riunet.upv.es/handle/10251/51078es_ES
dc.description.issue1-2es_ES
dc.description.sponsorshipThe authors extend their appreciation to the Research Centre, College of Applied Medical Sciences and the Deanship of Scientific Research at King Saud University for funding this research.
dc.description.upvformatpfin133es_ES
dc.description.upvformatpinicio109es_ES
dc.description.volume22es_ES
dc.embargo.lift10000-01-01
dc.embargo.termsforeveres_ES
dc.identifier.eissn1552-0633
dc.identifier.issn1551-9899
dc.identifier.urihttps://riunet.upv.es/handle/10251/51078
dc.languageIngléses_ES
dc.publisherOld City Publishinges_ES
dc.relation.ispartofAdhoc and Sensor Wireless Networkses_ES
dc.relation.senia287260
dc.rightsReserva de todos los derechoses_ES
dc.rights.accessRightsCerradoes_ES
dc.subjectWireless sensor networkes_ES
dc.subjectSecurityes_ES
dc.subjectEnergy exhaustion attackes_ES
dc.subjectClusteres_ES
dc.subjectEnergy harvestinges_ES
dc.subjectArtificial neural networkes_ES
dc.subject.classificationINGENIERIA TELEMATICAes_ES
dc.titleArtificial neural network based detection of energy exhaustion attacks in wireless sensor networks capable of energy harvestinges_ES
dc.typeArtículoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
person.identifier260345
person.identifier.orcid0000-0002-0862-0533
relation.isAuthorOfPublicatione6f912f7-e605-4217-ac55-555ebb925e03
relation.isAuthorOfPublication.latestForDiscoverye6f912f7-e605-4217-ac55-555ebb925e03
relation.isOrgUnitOfPublication02a0f2c5-c452-4e1d-a7d9-b731347d078c
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upv.uuid03e5f0f9-d1fa-4f4a-92da-0a88f24bc931es_ES

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