Deep Learning Based Neural Network Model for Anomaly Detection in Automobile Industry

Document Type : Primary Research paper


1 Bannari Amman Institute of Technology, Sathyamangalam, Erode

2 PSG College of Technology, Coimbatore


Because of the recent advancement in the technologies like Internet of things and
Artificial Intelligence, most of the industries have adapted into automation. In our routine
life most of the devices have become automated one with the help of more connectivity and
flawless integration of information technology. Most of the modern vehicles are equipped
with smart technologies with security concepts. To identify the abnormality in vehicle network,
an anomaly detection mechanism is proposed in this paper. By using this anomaly
detection system we are able distinguish the vehicular attacks in the networks and also able
to detect the manufacturing defects for ensuring the quality assurance. Due his paper describes
a deep learning based neural network model that will explore the abnormalities in
the vehicular network data. Various steps in the neural network implementation part have
been illustrated. It also evaluates the experimental results by applying the deep learning
method on the given real-time data. Due to the immediate responsiveness of the system, it
has been gaining much more attention in the automobile industry.


Volume 12, Issue 3 - Serial Number 3
ICMMNT-2021 International Virtual Conference on Materials, Manufacturing and Nanotechnology, 30th June, 2021.
June 2021
Pages 1712-1717