Cybersecurity of Connected and Autonomous Vehicles (CAVs): Deployment in Smart Cities

Connected and Autonomous Vehicles (CAVs) have the potential to expedite the realization of a smart city. This convergence of three technologies, namely wireless connectivity, automation, and electrification, creates a vehicle that is capable of self-driving and parking, sharing and storing digital content, sensing and monitoring its surroundings, and mobilizing electrical power. In a smart city, these capabilities can be translated into various kind of services. However, the provisioning of these services will be challenging due to different issues as well as the human fear and trust in this technology. The goals of this project are to devise an Integrated Service Management Framework (ISMF) which integrates a set of AI algorithmic techniques to ultimately secure self-driving vehicles for the betterment of smart city services and applications.

2 Members

Supervisors

Students

  • Farkhanda Zafar Raja: COMSATS University, Pakistan

2 Publication

Journal Articles

S Zafar, S Jangsher, O Bouachir, M Aloqaily, J Ben Othman. QoS enhancement with deep learning-based interference prediction in mobile IoT. Computer Communications 148. 10.1016/j.comcom.2019.09.010.
O Bouachir, M Aloqaily, I Al Ridhawi, O Alfandi, HB Salameh UAV-Assisted Vehicular Communication for Densely Crowded Environments. 2020 IEEE/IFIP Network Operations and Management Symposium, Budapest, Hungary, 2020, pp. 1-4, doi: 10.1109/NOMS47738.2020.9110438.

Conference Papers

O Bouachir, M Aloqaily, F Garcia, N Larrieu, and T Gayraud. Testbed of QoS Ad-Hoc Network Designed for Cooperative Multi-drone Tasks. In Proceedings of the 17th ACM International Symposium on Mobility Management and Wireless Access (MobiWac ’19). 2019. Association for Computing Machinery, New York, NY, USA, 89–95. DOI:https://doi.org/10.1145/3345770.3356740
S Zafar, S Jangsher, M Aloqaily, O Bouachir, J Ben Othman Resource allocation in moving small cell network using deep learning based interference determination