Database Management Systems in Autonomous Vehicles: Ensuring Data Integrity and Security in ADAS

EasyChair Preprint 14878

Abstract

The integration of Autonomous Vehicles (AVs) with Advanced Driver Assistance Systems (ADAS) has brought forward a growing need for efficient and secure data management solutions. ADAS relies on real-time data from a variety of sources, including sensors, vehicle networks, and cloud-based services, to make split-second decisions. In this context, Database Management Systems (DBMS) play a critical role in storing, retrieving, and processing massive volumes of data, ensuring that information flows seamlessly and securely. However, the complexity of autonomous driving environments presents significant challenges, particularly in ensuring data integrity, availability, and security. This research explores the role of DBMS in AVs, focusing on methods to maintain data integrity and security within ADAS. It evaluates current database architectures, encryption techniques, and fault tolerance mechanisms, while also proposing novel solutions for securing in-vehicle databases from potential cyber threats. The study highlights the importance of optimizing data management frameworks to ensure that AVs operate safely and effectively in real-world scenarios.

Keyphrases: • Advanced Driver Assistance Systems (ADAS), • Autonomous Vehicles (AVs), • Data Integrity, • Data Security, • Database Management Systems (DBMS), • In-vehicle Databases, • Real-time Data Processing

@booklet{EasyChair:14878,
  author    = {Adeoye Qudus},
  title     = {Database Management Systems in Autonomous Vehicles: Ensuring Data Integrity and Security in ADAS},
  howpublished = {EasyChair Preprint 14878},
  year      = {EasyChair, 2024}}