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Efficient feature selection for intrusion detection systems with priority queue-based GRASP

2024-12-31Conference object Open access
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dc.contributor.authorQuincozes, Vagner E.
dc.contributor.authorQuincozes, Silvio E.
dc.contributor.authorAlbuquerque, Célio
dc.contributor.authorPassos, Diego
dc.contributor.authorMassé, Daniel
dc.date.accessioned2025-01-07T10:56:35Z
dc.date.available2025-01-07T10:56:35Z
dc.date.issued2024-12-31
dc.description.abstractThe Greedy Randomized Adaptive Search Proce dure for Feature Selection (GRASP-FS) is a recently-proposed metaheuristic that optimizes the feature selection process for Intrusion Detection Systems (IDS) by combining exploration and refinement techniques for more assertive intrusion detection. However, GRASP-FS may be time and resource-consuming for large datasets. In this work, we propose GRASPQ-FS, an extended version of GRASP-FS using Priority Queues to reduce resource consumption and processing time. As an additional contribution, we provide a comprehensive analysis of the most suitable parameters for our RASPQ-FS. Our results reveal that GRASPQ-FS can speed up feature selection up to 90% over GRASP-FS, without compromising F1-Score. Also, we observed that a priority queue with 50 solutions saved 50% in execution time while increasing the F1-Score by 4.5%.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationQuincozes V. E., Quincozes S. E., Albuquerque C., Passos D., Massé D.. Efficient Feature Selection for Intrusion Detection Systems with Priority Queue-Based GRASP, 2024 IEEE 13th International Conference on Cloud Networking (CloudNet), Rio de Janeiro, Brazil, 2024, pp. 1-8, doi: 10.1109/CloudNet62863.2024.10815746pt_PT
dc.identifier.doi10.1109/CloudNet62863.2024.10815746pt_PT
dc.identifier.eissn2771-5663
dc.identifier.isbn979-8-3503-7656-2
dc.identifier.isbn979-8-3503-7657-9
dc.identifier.issn2374-3239
dc.identifier.urihttp://hdl.handle.net/10400.21/18126
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relation.publisherversionhttps://ieeexplore.ieee.org/abstract/document/10815746pt_PT
dc.subjectIntrusion Detection System (IDS)pt_PT
dc.subjectFeature Selectionpt_PT
dc.subjectGRASPpt_PT
dc.subjectCyber-Physical System (CPS)pt_PT
dc.titleEfficient feature selection for intrusion detection systems with priority queue-based GRASPpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlace27-29 November 2024 - Rio de Janeiro, Brazilpt_PT
oaire.citation.endPage8pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title2024 IEEE 13th International Conference on Cloud Networking (CloudNet)pt_PT
person.familyNameQuincozes
person.familyNameEreno Quincozes
person.familyNameAlbuquerque
person.familyNamePassos
person.givenNameVagner
person.givenNameSilvio
person.givenNameCélio
person.givenNameDiego
person.identifier.orcid0000-0002-6688-5572
person.identifier.orcid0000-0001-6793-4033
person.identifier.orcid0000-0002-7959-6569
person.identifier.orcid0000-0002-9707-1176
person.identifier.ridACS-4328-2022
person.identifier.ridO-4975-2015
person.identifier.scopus-author-id57773301200
person.identifier.scopus-author-id57191616602
person.identifier.scopus-author-id15836551100
person.identifier.scopus-author-id24478915900
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication543a9e4e-85a2-4f78-b3e2-9bc970c07de3
relation.isAuthorOfPublicationbd52eb9a-ae55-4389-8950-934670c79c03
relation.isAuthorOfPublication7123bd56-5154-4351-bc80-e5c8bbacf15a
relation.isAuthorOfPublication1baae68b-74ca-4d47-9c93-d990147ada03
relation.isAuthorOfPublication.latestForDiscovery1baae68b-74ca-4d47-9c93-d990147ada03

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