An In-Depth Review of Secure Drone Communication-Based Technologies

Abstract

The security of drones has become a crucial topic among researchers and industry professionals. While drones have numerous applications, failing to address security challenges and make necessary architectural adjustments may hinder their effectiveness in future implementations. This paper provides a comprehensive review of security-sensitive drone applications and the associated risks in drone communication, including denial-of-service (DoS) attacks, man-in-the-middle attacks, de-authentication attacks, and others. Additionally, we explore potential solution architectures that leverage emerging technologies such as Blockchain, Machine Learning (ML), and Neutrosophic. Given that drones are often resource-constrained devices, deploying heavy security algorithms on board is impractical. Instead, Blockchain can be utilised to securely store all data transmitted to and from the drones, protecting it from tampering and eavesdropping. Various ML algorithms can be employed to identify malicious drones within the network and determine safe flight paths. Furthermore, Neutrosophic methods can enhance the reliability of drone networks by modelling the inherent uncertainties and variabilities involved in wireless communications and drone operations, enhancing the ability to evaluate risks and vulnerabilities effectively, while blockchain can provide computational resources closer to the drones, thus preventing overload.