Creating a Secure Autonomous Vehicle System Using a Neuro-Fuzzy System that Merges Artificial Neural Networks and Fuzzy Interface Systems

Douzi, Ahmed and Lukács, Judit (2024) Creating a Secure Autonomous Vehicle System Using a Neuro-Fuzzy System that Merges Artificial Neural Networks and Fuzzy Interface Systems. YBL JOURNAL OF BUILT ENVIRONMENT, 9 (2). pp. 1-9. ISSN 2063-997X

Preview

Text indecs2025-pp95-104.pdf - Published Version Available under License Creative Commons Attribution. Download (851kB) | Preview

Abstract

Unmanned Aerial Systems (UAS) and Unmanned Aerial Vehicles (UAV) are increasingly susceptible to cybersecurity threats, posing significant risks to flight safety and operational integrity. This article presents a comprehensive study of the cybersecurity challenges faced by UAS and UAV, emphasizing their vulnerability to cyber-attacks due to reliance on wireless communications and remote operations. The potential impacts of cyber threats on UAS and UAV, including financial losses and operational disruptions, are examined. Furthermore, the article discusses ongoing investigations and regulatory measures aimed at integrating cybersecurity and physical security protocols to mitigate credible threats to national security and public safety. By addressing these critical issues, this article aims to contribute to the understanding of cybersecurity in the context of unmanned aerial platforms, providing insights into the evolving landscape of cyber threats and the measures required to ensure the safe and secure operation of unmanned aerial systems. This article provides a short overview of the key focus areas including the cybersecurity challenges, potential impacts, ongoing studies, and regulatory measures related to UAS and UAV.

Actions (login required)

Edit Item