Detection of malicious UAVs based on secure authentication over the Internet of Drones (IoD)

The Internet of Drones (IoD) is experiencing significant growth across military, commercial, and civilian applications due to its unique attributes, including high mobility and three-dimensional movement. However, the reliance on unencrypted wireless communication and the limited computational capabilities of drones makes them vulnerable to various cyber-attacks. These vulnerabilities expose IoD networks to threats such as man-in-the-middle attacks, impersonation, credential leakage, GPS spoofing, and drone hijacking. To address these challenges, the development of a robust and highly secure protocol is essential. This paper presents an innovative approach for detecting malicious drones utilizing the Conversation to Handshake Authentication (CTHA) method. Our proposed solution employs sequential procedures and deep learning techniques to distinguish between legitimate and malicious drones effectively. Furthermore, we incorporate blockchain technology and federated learning to enhance data integrity and resilience against attacks, such as Denial of Service (DoS) attacks. The objective of our solution is to bolster the security and operational integrity of IoD systems. Extensive experimentation validates the effectiveness and accuracy of our proposed method. The findings of this research contribute to the evolving field of UAV security, establishing a foundation for proactive defense mechanisms against malicious activities within the IoD ecosystem.