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BiLSTM-Attention Seeking Intrusion Detection System for SWIPT-Enabled IoT Systems

2026-05-05Documento de conferência Acesso aberto
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dc.contributor.authorSooriarachchi, Vishalya
dc.contributor.authorJayakody, Dushantha
dc.contributor.authorPanic, Stefan
dc.contributor.institutionUNINOVA-Instituto de Desenvolvimento de Novas Tecnologias
dc.contributor.institutionCTS - Centro de Tecnologia e Sistemas
dc.date.accessioned2026-07-17T13:23:02Z
dc.date.available2026-07-17T13:23:02Z
dc.date.issued2026-05-05
dc.descriptionPublisher Copyright: © 2025 Copyright held by the owner/author(s).
dc.description.abstractIntegration of simultaneous wireless information and power transfer (SWIPT) into Internet of Things (IoT) network require unique security requirements. These systems operate in energy-constrained environments, where traditional intrusion detection systems (IDS) are mostly unable to perform as expected. In SWIPT-systems, information transmission as well as energy harvesting and allocation systems are vulnerable to attacks, thereby requiring more sophisticated security systems to support continued operation. The study proposes an unsupervised BiLSTM attention autoencoder-based IDS model designed specifically for SWIPT-enabled IoT systems operating with a sequence-to-sequence framework.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent5
dc.format.extent1131286
dc.identifier.doi10.1145/3789692.3789844
dc.identifier.isbn9798400720918
dc.identifier.otherPURE: 168536929
dc.identifier.otherPURE UUID: 84caaa89-beae-4fa4-b580-f264546adc00
dc.identifier.otherScopus: 105039848098
dc.identifier.urihttp://hdl.handle.net/10362/204643
dc.identifier.urlhttps://www.scopus.com/pages/publications/105039848098
dc.language.isoeng
dc.peerreviewedyes
dc.publisherACM - Association for Computing Machinery
dc.subjectBiLSTM
dc.subjectIntrusion detection systems
dc.subjectIoT
dc.subjectSWIPT
dc.subjectUnsupervised learning
dc.subjectComputer Networks and Communications
dc.subjectInformation Systems
dc.subjectArtificial Intelligence
dc.subjectHardware and Architecture
dc.titleBiLSTM-Attention Seeking Intrusion Detection System for SWIPT-Enabled IoT Systemsen
dc.typeconference object
degois.publication.firstPage1168
degois.publication.lastPage1172
degois.publication.titleICFNDS '25
degois.publication.title9th International Conference on Future Network and Distributed System, ICFNDs 2025
dspace.entity.typePublication
rcaap.rightsopenAccess

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