Vol. 3 No. 1 (2023): African Journal of Artificial Intelligence and Sustainable Development
Articles

From Tactile Buttons to Digital Orchestration: A Paradigm Shift in Vehicle Control with Smartphone Integration and Smart UI – Unveiling Cybersecurity Vulnerabilities and Fortifying Autonomous Vehicles with Adaptive Learning Intrusion Detection Systems

Vamsi Vemoori
Systems Integration Technical Expert - ADAS/AD, Robert Bosch, Plymouth-MI, USA
Cover

Published 12-03-2023

Keywords

  • Intuitive Interfaces,
  • Adaptive Learning Techniques,
  • Digital Controls,
  • Smartphone Applications,
  • Key Card Systems,
  • Flipper Zero Device,
  • Cybersecurity,
  • Autonomous Vehicles,
  • Intrusion Detection Systems,
  • Connected Car Security
  • ...More
    Less

How to Cite

[1]
V. Vemoori, “From Tactile Buttons to Digital Orchestration: A Paradigm Shift in Vehicle Control with Smartphone Integration and Smart UI – Unveiling Cybersecurity Vulnerabilities and Fortifying Autonomous Vehicles with Adaptive Learning Intrusion Detection Systems”, African J. of Artificial Int. and Sust. Dev., vol. 3, no. 1, pp. 54–91, Mar. 2023, Accessed: Dec. 22, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/24

Abstract

The transportation landscape is undergoing a metamorphosis, propelled by the burgeoning advancements in automotive technology. At the forefront of this revolution lies the rise of Advanced Vehicles (AVs), vehicles imbued with an unprecedented level of automation that empowers drivers with unparalleled control and convenience. This paper delves into this transformative journey, meticulously dissecting the transition from traditional vehicles reliant on a myriad of physical buttons to the sleek and intuitive interfaces that characterize contemporary AVs. This shift from the tactile to the digital realm empowers users to effortlessly manipulate various aspects of the vehicle's operation, encompassing climate control, entertainment systems, and even the initiation of the startup process, all at their fingertips.

A comparative analysis is undertaken to illuminate the safety enhancements ushered in by digital controls. The efficacy of modern AVs, with their emphasis on intuitive interfaces and haptic feedback, is meticulously evaluated against their conventional counterparts. This analysis sheds light on how digital controls can potentially minimize human error and reaction times, thereby enhancing overall driving safety.

The discourse then meticulously dissects the critical consideration of cybersecurity within the ever-evolving realm of AVs. The interconnected nature of modern vehicles introduces a unique set of vulnerabilities. This section meticulously examines the inherent weaknesses present in smartphone applications and key card systems, both of which are increasingly being integrated into AVs. A comprehensive evaluation is conducted to assess their susceptibility to potential hacking threats, encompassing unauthorized access, manipulation of vehicle control systems, and data breaches.

Furthermore, the paper delves into the emerging threat landscape, specifically focusing on novel technologies like the Flipper Zero device. This versatile tool presents a double-edged sword for the automotive cybersecurity landscape. While it holds immense promise for ethical hackers and security researchers, the potential for malicious actors to exploit its capabilities for nefarious purposes cannot be ignored. This section meticulously dissects the functionalities of the Flipper Zero device and its potential impact on the security of AVs.

The culmination of this paper underscores the absolute imperative of robust cybersecurity measures in safeguarding the integrity and safety of modern AVs. A secure future for autonomous vehicles hinges upon the development and implementation of comprehensive cybersecurity solutions. This section advocates for a multi-pronged approach, encompassing not only the technological aspects but also the behavioral and regulatory dimensions. By fostering a culture of cybersecurity awareness among users, coupled with the development of cutting-edge intrusion detection systems and robust regulatory frameworks, we can ensure the continued advancement and adoption of AVs in a secure and trustworthy manner.

The paper concludes by proposing a novel approach to fortifying AV cybersecurity – Adaptive Learning Intrusion Detection Systems (AL-IDS). This innovative system leverages the power of machine learning to continuously learn and adapt to evolving cyber threats. The AL-IDS would be meticulously designed to analyze network traffic, user behavior, and system anomalies in real-time, enabling the identification and mitigation of potential attacks with unprecedented accuracy.

Downloads

Download data is not yet available.

References

  1. Atighet, R. R., & Ayoub, M. (2018, December). A survey on intrusion detection systems in vehicular ad hoc networks. In 2018 IEEE Global Communications Conference (GLOBECOM) (pp. 1-6). IEEE.
  2. Choi, H., Kim, H., & Kim, J. (2017, July). Honeynet-based anomaly detection system for in-vehicle networks. In 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 2748-2753). IEEE.
  3. Eizadi, E., Choo, K. K. R., & Abdullah, A. H. (2019). A review on engineering secure connected vehicles. IEEE Communications Surveys & Tutorials, 21(4), 3223-3243.
  4. Gao, D., Xiang, Y., & An, S. (2019, December). A survey of intrusion detection techniques in vehicular ad-hoc networks. In 2019 IEEE International Conference on Computational Science and Engineering (CSE) (pp. 1227-1232). IEEE.
  5. Hamida, F. B., & Aissaoui, M. (2016, December). Anomaly-based intrusion detection systems for securing vehicular ad-hoc networks. In 2016 11th International Conference on Soft Computing and Intelligent Systems (SCIS) (pp. 1-6). IEEE.
  6. Hao, J., Jing, B., Liang, X., Liu, H., & Li, C. (2018, August). Machine learning based intrusion detection for connected vehicles. In 2018 IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPDPA) (pp. 117-122). IEEE.
  7. Habibi, N., Fayez, M., & Boutaba, R. (2018, April). Survey of intrusion detection and prevention systems for connected vehicles. In 2018 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.
  8. Hubaux, J. Y., Petit, J., & Seys, S. (2004, October). On the security and privacy of in-vehicle networks. In Proceedings of the 2nd International Conference on Mobile Ad-Hoc Networking and Computing (MobiHoc) (pp. 160-170). ACM.
  9. Huang, Y., Liu, A., & Kang, B. H. (2017, July). A survey of security communication for connected vehicles. In 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 003218-003223). IEEE.
  10. Islam, N., Mahmud, M., Rivai, I. M., & Atiquzzaman, M. (2019, December). A survey on security and privacy of connected vehicles. In 2019 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) (pp. 1-6). IEEE.
  11. Jang, Y., Jo, M., & Kim, J. (2016, August). Security vulnerabilities of connected vehicles and countermeasures. In 2016 International Conference on Information Networking (ICOIN) (pp. 303-308). IEEE.
  12. Jo, M., Han, D., & Kim, J. (2017, July). Survey on the security threats of connected vehicles and countermeasures. In 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 003196-003201). IEEE.
  13. Khan, M. A., Al-Saleh, M. A., Al-Shaer, E., & Khan, A. (2014, March). A taxonomy of security vulnerabilities in connected vehicles. In 11th International Conference on Wireless Communications and Mobile Computing (IWCMC) (pp. 50-55). IEEE.
  14. Kim, J., & Kumar, V. (2016, December). A comprehensive survey of research on connected vehicle security. In 2016 13th International Conference on Wired and Wireless Internet Communication (WWIC) (pp. 1-6). IEEE.
  15. Kumari, S., & Gupta, B. B. (2019, March). Security requirements and challenges in connected vehicles. In 2019