RT dataset
T1 Original and processed dataset of malware propagation in IoT networks with a SIR epidemiological model
A1 Sainz Villegas, Leticia
A1 Casado Vara, Roberto Carlos
A1 Basurto Hornillos, Nuño
A1 Cambra Baseca, Carlos
A1 Urda Muñoz, Daniel
A1 Herrero Cosío, Álvaro
K1 Mathematical epidemiology
K1 Graph theory
K1 Malware propagation
K1 Data science
K1 IoT network
K1 Informática
K1 Computer science
K1 Inteligencia artificial
K1 Artificial intelligence
AB 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.
PB Universidad de Burgos
YR 2025
FD 2025-04-21
LK http://hdl.handle.net/10259/10508
UL http://hdl.handle.net/10259/10508
LA eng
NO 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.
DS Repositorio Institucional de la Universidad de Burgos
RD 04-jun-2025