SANTOS, G. A. M.; SANTOS, Gabriel Araújo Miranda.
Resumen:
This research proposes developing a machine learning model for identifying attacks in wireless networks using traffic data from the UNSW-NB15 dataset. Three distinct models will be trained, tested, and validated: Random Forests and Convolutional Neural Networks. The goal is to develop a model that can be adapted for the TinyML platform, enabling its implementation on devices with limited computational resources.
