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https://hdl.handle.net/10495/45192Registro completo de metadatos
| Campo DC | Valor | Lengua/Idioma |
|---|---|---|
| dc.contributor.advisor | Múnera Ramírez, Danny Alexandro | - |
| dc.contributor.advisor | Tobón Vallejo, Diana Patricia | - |
| dc.contributor.author | Rodríguez López, Martha Lucía | - |
| dc.date.accessioned | 2025-02-24T21:24:50Z | - |
| dc.date.available | 2025-02-24T21:24:50Z | - |
| dc.date.issued | 2025 | - |
| dc.identifier.uri | https://hdl.handle.net/10495/45192 | - |
| dc.description.abstract | ABSTRACT : This thesis presents an IIoT Anomaly Classification Framework designed to detect and categorize anomalies, including failures, attacks, and other significant events. The research addresses the critical need for robust anomaly detection and classification in IIoT systems by providing a comprehensive and scalable solution adaptable to various industrial contexts. The framework enhances modern industrial operations’ reliability, security, and efficiency, paving the way for more resilient and intelligent IIoT systems. | spa |
| dc.format.extent | 172 páginas | spa |
| dc.format.mimetype | application/pdf | spa |
| dc.language.iso | eng | spa |
| dc.type.hasversion | info:eu-repo/semantics/draft | spa |
| dc.rights | info:eu-repo/semantics/openAccess | spa |
| dc.subject.lcsh | Anomaly detection (Computer security) | spa |
| dc.subject.lcsh | Detección de anomalías (Seguridad informática) | spa |
| dc.title | Anomaly Classification in Industrial Internet of Things | spa |
| dc.type | info:eu-repo/semantics/doctoralThesis | spa |
| dc.publisher.group | Intelligent Information Systems Lab. | spa |
| oaire.version | http://purl.org/coar/version/c_b1a7d7d4d402bcce | spa |
| dc.rights.accessrights | http://purl.org/coar/access_right/c_abf2 | spa |
| thesis.degree.name | Doctor en Ingeniería Electrónica y de la Computación | spa |
| thesis.degree.level | Doctorado | spa |
| thesis.degree.discipline | Facultad de Ingeniería. Doctorado en Ingeniería Electrónica y de Computación | spa |
| thesis.degree.grantor | Universidad de Antioquia | spa |
| dc.rights.creativecommons | https://creativecommons.org/licenses/by-nc-sa/4.0/ | spa |
| dc.publisher.place | Medellín, Colombia | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | spa |
| dc.type.redcol | https://purl.org/redcol/resource_type/TD | spa |
| dc.type.local | Tesis/Trabajo de grado - Monografía - Doctorado | spa |
| dc.subject.lemb | Seguridad en computadores | - |
| dc.subject.lemb | Computer security | - |
| dc.subject.lemb | Confiabilidad (ingeniería) | - |
| dc.subject.lemb | Reliability (engineering) | - |
| dc.subject.agrovoc | Internet de las cosas | - |
| dc.subject.agrovoc | Internet of things | - |
| dc.subject.proposal | Industrial Internet of Things (IIoT) | spa |
| dc.subject.agrovocuri | http://aims.fao.org/aos/agrovoc/c_e4315b22 | - |
| dc.subject.lcshuri | http://id.loc.gov/authorities/subjects/sh2005007675 | spa |
| dc.description.researchgroupid | COL0025934 | spa |
| Aparece en las colecciones: | Doctorados de la Facultad de Ingeniería | |
Ficheros en este ítem:
| Fichero | Descripción | Tamaño | Formato | |
|---|---|---|---|---|
| RodriguezMartha_2025_AnomalyClassificationIIoT | Tesis doctoral | 4.88 MB | Adobe PDF | Visualizar/Abrir |
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