Deep Learning Based Neural Network Model for Anomaly Detection in Automobile Industry
K Ganagavalli, Dr.Santhi. V, V. Krishnamoorthy · Int. J. of Aquatic Science · 2021
Because of the recent advancement in the technologies like Internet of things andArtificial Intelligence, most of the industries have adapted into automation. In our routinelife most of the devices have become automated one with the help of more connectivity andflawless integration of information technology. Most of the modern vehicles are equippedwith smart technologies with security concepts. To identify the abnormality in vehicle network,an anomaly detection mechanism is proposed in this paper. By using this anomalydetection system we are able distinguish the vehicular attacks in the networks and also ableto detect the manufacturing defects for ensuring the quality assurance. Due his paper describesa deep learning based neural network model that will explore the abnormalities inthe vehicular network data. Various steps in the neural network implementation part havebeen illustrated. It also evaluates the experimental results by applying the deep learningmethod on the given real-time data. Due to the immediate responsiveness of the system, ithas been gaining much more attention in the automobile industry.