Supervised and Unsupervised Data Engineering for Multimedia Data

4Automotive Vehicle Data Security Service in IoT Using ACO Algorithm

Sivanantham, K.^* and Blessington Praveen, P.

HCL Technologies, Coimbatore and Crapersoft, Coimbatore, India

Abstract

This study delves into the security concerns surrounding data generated by connected cars, encompassing information such as position, engine status, speed, and more. The term “Automotive IoT” refers to an advanced network of devices, including sensors, cameras, and GPS trackers, connected to the cloud to provide real-time data for enhancing manufacturing and transportation processes. Data is transmitted through electronic control units (ECUs), controller area networks (CANs), and in-car infotainment systems. Vehicle Data Collection systems efficiently gather, convert, and transfer vehicle data to the cloud, enabling companies to develop cutting-edge applications using data-driven analytics and machine learning to enhance vehicle quality, safety, and autonomy. However, the study highlights that nearly all data in and around connected vehicles is subject to data protection laws, particularly when associated with the vehicle’s registration or identification number. The integration of radar and video sensors in autonomous emergency braking is explained, emphasizing the importance of data security within self-driving cars. The study introduces the Ant colony optimization (ACO) algorithm as a means to protect car data from unauthorized access. The increasing deployment of autonomous vehicles on public ...