Original and processed dataset of malware propagation in IoT networks with a SIR epidemiological model

Sainz Villegas, Leticia; Casado Vara, Roberto Carlos; Basurto Hornillos, Nuño; Cambra Baseca, Carlos; Urda Muñoz, Daniel; Herrero Cosío, Álvaro

doi:10.71486/r4de-dj18

dc.contributor.author	Sainz Villegas, Leticia
dc.contributor.author	Casado Vara, Roberto Carlos
dc.contributor.author	Basurto Hornillos, Nuño
dc.contributor.author	Cambra Baseca, Carlos
dc.contributor.author	Urda Muñoz, Daniel
dc.contributor.author	Herrero Cosío, Álvaro
dc.coverage.spatial	north=42.35; west=-3.706667; name=Burgos, Spain
dc.coverage.temporal	start=2025-04; end=2025-04
dc.date.accessioned	2025-05-29T11:52:40Z
dc.date.available	2025-05-29T11:52:40Z
dc.date.issued	2025-04-21
dc.identifier.uri	http://hdl.handle.net/10259/10508
dc.description.abstract	The dataset contains the data generated by an individual SIR model in an IoT network simulated by a graph for 20 time steps. This dataset is designed for training graph-based AI models for malware propagation detection in IoT networks.	en
dc.description.sponsorship	This publication is part of the AI4SECIoT project ("Artificial Intelligence for Securing IoT Devices"), funded by the National Cybersecurity Institute (INCIBE), derived from a collaboration agreement signed between the National Institute of Cybersecurity (INCIBE) and the University of Burgos. This initiative is carried out within the framework of the Recovery, Transformation and Resilience Plan funds, financed by the European Union (Next Generation), the project of the Government of Spain that outlines the roadmap for the modernization of the Spanish economy, the recovery of economic growth and job creation, for solid, inclusive and resilient economic reconstruction after the COVID19 crisis, and to respond to the challenges of the next decade.	en
dc.format.mimetype	image/png
dc.format.mimetype	text/csv
dc.format.mimetype	text/plain
dc.language.iso	eng	es
dc.publisher	Universidad de Burgos	es
dc.rights	Atribución 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	*
dc.subject	Mathematical epidemiology	en
dc.subject	Graph theory	en
dc.subject	Malware propagation	en
dc.subject	Data science	en
dc.subject	IoT network	en
dc.subject.other	Informática	es
dc.subject.other	Computer science	en
dc.subject.other	Inteligencia artificial	es
dc.subject.other	Artificial intelligence	en
dc.title	Original and processed dataset of malware propagation in IoT networks with a SIR epidemiological model	en
dc.type	dataset	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es
dc.identifier.doi	10.71486/r4de-dj18
dc.relation.projectID	info:eu-repo/grantAgreement/INCIBE//AI4SECIoT/ES/Artificial Intelligence for Securing IoT Devices/	es
dc.type.hasVersion	info:eu-repo/semantics/acceptedVersion	es
dc.publication.year	2025