Mostrar el registro sencillo del ítem
Anomaly detection of security threats to cyber-physical systems: a study
| dc.contributor.author | Jeffrey, N. | |
| dc.contributor.author | Tan, Q. | |
| dc.contributor.author | Villar Flecha, José Ramón | |
| dc.date.accessioned | 2023-03-02T09:29:53Z | |
| dc.date.available | 2023-03-02T09:29:53Z | |
| dc.date.issued | 2023 | |
| dc.identifier.isbn | 9783031180491 | |
| dc.identifier.issn | 2367-3370 | |
| dc.identifier.uri | http://hdl.handle.net/10651/66676 | |
| dc.description | International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) (17th. 2022. Salamanca, Spain) | |
| dc.description.sponsorship | This research has been funded by the SUDOE Interreg Program -grant INUNDATIO-, by the Spanish Ministry of Economics and Industry, grant PID2020-112726RB-I00, by the Spanish Research Agency (AEI, Spain) under grant agreement RED2018-102312-T (IA-Biomed), and by the Ministry of Science and Innovation under CERVERA Excellence Network project CER-20211003 (IBERUS) and Missions Science and Innovation project MIG-20211008 (INMERBOT). Also, by Principado de Asturias, grant SV-PA-21-AYUD/2021/50994. | |
| dc.format.extent | p. 3-12 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022). Salamanca, Spain, September 5–7, 2022, Proceedings | |
| dc.rights | © 2023 The authors, under exclusive license to Springer Nature Switzerland AG | |
| dc.rights | CC Reconocimiento – No Comercial – Sin Obra Derivada 4.0 Internacional | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.source | Scopus | |
| dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141655009&doi=10.1007%2f978-3-031-18050-7_1&partnerID=40&md5=a28c59bd49ac21be72b1ceb228c6011b | |
| dc.title | Anomaly detection of security threats to cyber-physical systems: a study | |
| dc.type | conference output | spa |
| dc.identifier.doi | 10.1007/978-3-031-18050-7_1 | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-112726RB-I00/ES/INTELIGENCIA COMPUTACIONAL PARA LA MITIGACION DE EMISIONES: NUEVAS METODOLOGIAS DE APRENDIZAJE CON DATOS INCOMPLETOS/ | |
| dc.relation.projectID | RED2018-102312-T | |
| dc.relation.projectID | CER-20211003 | |
| dc.relation.projectID | SV-PA-21-AYUD/2021/50994 | |
| dc.relation.projectID | MIG-20211008 | |
| dc.relation.publisherversion | http://dx.doi.org/10.1007/978-3-031-18050-7_1 | |
| dc.rights.accessRights | open access | |
| dc.type.hasVersion | AM |
Ficheros en el ítem
Este ítem aparece en la(s) siguiente(s) colección(ones)
-
Informática [813]
-
Investigaciones y Documentos OpenAIRE [8087]
Publicaciones resultado de proyectos financiados con fondos públicos -
Ponencias, Discursos y Conferencias [4066]
Este ítem está sujeto a una licencia Creative Commons