Cyberattacks Predictions Workflow using Machine Learning
This research aims to validate the effectiveness of a machine learning model composed of three classifiers: decision tree, logistic regression, and support vector machines. Through the design of a workflow, we demonstrate the effectiveness of the model. First, we execute a network attack, and then m...
- Autores:
-
Barrera Pérez, Carlos Eduardo
Serrano, Jairo E.
Martinez-Santos, Juan Carlos
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/12335
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/12335
- Palabra clave:
- Denial-Of-Service Attack;
DDoS;
Attack
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
| Summary: | This research aims to validate the effectiveness of a machine learning model composed of three classifiers: decision tree, logistic regression, and support vector machines. Through the design of a workflow, we demonstrate the effectiveness of the model. First, we execute a network attack, and then monitoring, processing, storage, visualization, and data transfer tools are implemented to create the most realistic environment possible and obtain more accurate predictions. © 2021 IEEE. |
|---|