2026-04-23T00:42:24Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/72432023-02-01T13:30:06Zcom_10259_3847com_10259_5086com_10259_2604col_10259_3848

Vega Vega, Rafael Alejandro b2614eb6-35c7-470d-8b77-ce348cba3477 600 Chamoso, Pablo d1ca1a66-6467-4286-95dd-6b5c19c87f50 600 González Briones, Alfonso 0224405b-0157-4701-af56-11036f89c966 600 Casteleiro-Roca, José-Luis 61f65533-5bcc-463c-99de-bb093f5b34d3 600 Jove, Esteban 7141acd0-36d9-40b1-b113-3b6548042ede 600 Meizoso-López, María del Carmen b9b3fc62-0602-468f-9424-4ec95a49c338 600 Rodríguez-Gómez, Benigno Antonio 555167f1-cea0-4db4-95d5-5a6e8524339e 600 Quintián, Héctor 24df8f20-cf82-40f8-a3bc-a762add5e4b4 600 Herrero Cosío, Álvaro 283 600 0000-0002-2444-5384 Matsui, Kenji 79a45e3d-b89a-4c5a-bc50-12b1bdedb2b4 600 Corchado, Emilio 125 600 0000-0001-8560-3991 Calvo-Rolle, José Luis 2fa3782f-36e0-43f7-8aa1-68eadc78465c 600 2023-01-13T13:51:06Z 2023-01-13T13:51:06Z 2020-03 http://hdl.handle.net/10259/7243 10.3390/app10072276 2076-3417 The present research work focuses on overcoming cybersecurity problems in the Smart Grid. Smart Grids must have feasible data capture and communications infrastructure to be able to manage the huge amounts of data coming from sensors. To ensure the proper operation of next-generation electricity grids, the captured data must be reliable and protected against vulnerabilities and possible attacks. The contribution of this paper to the state of the art lies in the identification of cyberattacks that produce anomalous behaviour in network management protocols. A novel neural projectionist technique (Beta Hebbian Learning, BHL) has been employed to get a general visual representation of the traffic of a network, making it possible to identify any abnormal behaviours and patterns, indicative of a cyberattack. This novel approach has been validated on 3 different datasets, demonstrating the ability of BHL to detect different types of attacks, more effectively than other state-of-the-art methods. TEACHING STAFF MOBILITY UNDER BILATERAL AGREEMENTS (University of Salamanca—Osaka Institute of Technology 2019). application/pdf eng MDPI Applied sciences. 2020, V. 10, n. 7, e2276 https://doi.org/10.3390/app10072276 Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Smart grid Computational intelligence Automatic response Exploratory projection pursuit Neural network Informática Computer science Intrusion Detection with Unsupervised Techniques for Network Management Protocols over Smart Grids info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Applied Sciences 10 7 THUMBNAIL Herrero-as_2020.pdf.jpg Herrero-as_2020.pdf.jpg IM Thumbnail image/jpeg 3252 https://riubu.ubu.es/bitstream/10259/7243/4/Herrero-as_2020.pdf.jpg c3f4444fa3d2f14fbeba71e85e4bc127 MD5 4 LICENSE license.txt license.txt text/plain; charset=utf-8 1362 https://riubu.ubu.es/bitstream/10259/7243/3/license.txt 5d013bfa6e473ff0db22cd82a4d71a70 MD5 3 CC-LICENSE license_rdf license_rdf application/rdf+xml; charset=utf-8 908 https://riubu.ubu.es/bitstream/10259/7243/2/license_rdf 0175ea4a2d4caec4bbcc37e300941108 MD5 2 ORIGINAL Herrero-as_2020.pdf Herrero-as_2020.pdf application/pdf 644923 https://riubu.ubu.es/bitstream/10259/7243/1/Herrero-as_2020.pdf 5ab814f2e69e0223544d2c839cc169cf MD5 1 10259/7243 oai:riubu.ubu.es:10259/7243 2023-02-01 14:30:06.038 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es 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