Herramienta de disección de tramas para protocolos IoT

  1. Narciandi-Rodríguez, Diego 1
  2. Aveleira-Mata, Jose 1
  3. Merayo Corcoba, Alicia 1
  4. Rubiños, Manuel 2
  5. Arcano-Bea, Paula 2
  6. Alaiz-Moretón, Héctor 1
  1. 1 Universidad de León
    info

    Universidad de León

    León, España

    ROR https://ror.org/02tzt0b78

  2. 2 Universidade da Coruña
    info

    Universidade da Coruña

    La Coruña, España

    ROR https://ror.org/01qckj285

Revista:
Jornadas de Automática
  1. Cruz Martín, Ana María (coord.)
  2. Arévalo Espejo, V. (coord.)
  3. Fernández Lozano, Juan Jesús (coord.)

ISSN: 3045-4093

Año de publicación: 2024

Número: 45

Tipo: Artículo

DOI: 10.17979/JA-CEA.2024.45.10804 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Resumen

In recent years, the emergence and use of IoT (Internet of Things) devices, which stand out for their use of light weight protocols due to their low computational load, has led to the emergence of new attack vectors in systems with IoT devices.This is why it is necessary to train and develop machine learning models from real data, which are implemented in intrusion detection systems (IDS). This is where datasets come in, which make this activity possible thanks to the effective developmentof these models. This paper presents the development of a frame dissector that facilitates the generation of specific datasets for the different existing IoT protocols that are useful to create machine learning models from them.

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Fuente de los datos: Dialnet