Publication
Efficient feature selection for intrusion detection systems with priority queue-based GRASP
dc.contributor.author | Quincozes, Vagner E. | |
dc.contributor.author | Quincozes, Silvio E. | |
dc.contributor.author | Albuquerque, Célio | |
dc.contributor.author | Passos, Diego | |
dc.contributor.author | Massé, Daniel | |
dc.date.accessioned | 2025-01-07T10:56:35Z | |
dc.date.available | 2025-01-07T10:56:35Z | |
dc.date.issued | 2024-12-31 | |
dc.description.abstract | The 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.version | info:eu-repo/semantics/publishedVersion | pt_PT |
dc.identifier.citation | Quincozes 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/CloudNet62863.2024.10815746 | pt_PT |
dc.identifier.doi | 10.1109/CloudNet62863.2024.10815746 | pt_PT |
dc.identifier.eissn | 2771-5663 | |
dc.identifier.isbn | 979-8-3503-7656-2 | |
dc.identifier.isbn | 979-8-3503-7657-9 | |
dc.identifier.issn | 2374-3239 | |
dc.identifier.uri | http://hdl.handle.net/10400.21/18126 | |
dc.language.iso | eng | pt_PT |
dc.publisher | IEEE | pt_PT |
dc.relation.publisherversion | https://ieeexplore.ieee.org/abstract/document/10815746 | pt_PT |
dc.subject | Intrusion Detection System (IDS) | pt_PT |
dc.subject | Feature Selection | pt_PT |
dc.subject | GRASP | pt_PT |
dc.subject | Cyber-Physical System (CPS) | pt_PT |
dc.title | Efficient feature selection for intrusion detection systems with priority queue-based GRASP | pt_PT |
dc.type | conference object | |
dspace.entity.type | Publication | |
oaire.citation.conferencePlace | 27-29 November 2024 - Rio de Janeiro, Brazil | pt_PT |
oaire.citation.endPage | 8 | pt_PT |
oaire.citation.startPage | 1 | pt_PT |
oaire.citation.title | 2024 IEEE 13th International Conference on Cloud Networking (CloudNet) | pt_PT |
person.familyName | Quincozes | |
person.familyName | Ereno Quincozes | |
person.familyName | Albuquerque | |
person.familyName | Passos | |
person.givenName | Vagner | |
person.givenName | Silvio | |
person.givenName | Célio | |
person.givenName | Diego | |
person.identifier.orcid | 0000-0002-6688-5572 | |
person.identifier.orcid | 0000-0001-6793-4033 | |
person.identifier.orcid | 0000-0002-7959-6569 | |
person.identifier.orcid | 0000-0002-9707-1176 | |
person.identifier.rid | ACS-4328-2022 | |
person.identifier.rid | O-4975-2015 | |
person.identifier.scopus-author-id | 57773301200 | |
person.identifier.scopus-author-id | 57191616602 | |
person.identifier.scopus-author-id | 15836551100 | |
person.identifier.scopus-author-id | 24478915900 | |
rcaap.rights | openAccess | pt_PT |
rcaap.type | conferenceObject | pt_PT |
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