This study focuses on driver-behavior identification and its application to finding embedded
solutions in a connected car environment. We present a lightweight, end-to-end deep …

The rapid expansion of intra-vehicle networks has increased the number of threats to such
networks. Most modern vehicles implement various physical and data-link layer …

A modern vehicle contains a large number of electronic control units and sensors that are
connected to cloud environments. These electronic units generate a huge amount of data …

We investigate the use of Machine Learning tools applied to driver identification. We
propose us ing Information Theory measures as features in Machine Learning models. The …

The rapid urbanization growth has underscored the need for innovative solutions to
enhance transportation efficiency and safety. Intelligent Transportation Systems (ITS) have …

Neste trabalho, propomos a identificação do comportamento do motorista com o uso do
algoritmo Random Forest e Long Short-Term Memory (LSTM), baseado em medidas de …