Abstract

During the last few years, a wide variety of Internet of Drones (IoD) applications have emerged with numerous heterogeneous aerial and ground network elements interconnected and equipped with advanced sensors, computation resources, and communication units. The evolution of IoD networks presupposes the mitigation of several security and privacy threats. Thus, robust authentication protocols should be implemented in order to attain secure operation within the IoD. However, owing to the inherent features of the IoD and the limitations of Unmanned Aerial Vehicles (UAVs) in terms of energy, computational, and memory resources, designing efficient and lightweight authentication solutions is a non-trivial and complicated process. Recently, the development of authentication mechanisms for the IoD has received unprecedented attention. In this paper, up-to-date research studies on authentication mechanisms for IoD networks are presented. To this end, the adoption of conventional technologies and methods, such as the widely used hash functions, Public Key Infrastructure (PKI), and Elliptic-Curve Cryptography (ECC), is discussed along with emerging technologies, including Mobile Edge Computing (MEC), Machine Learning (ML), and Blockchain. Additionally, this paper provides a review of effective hardware-based solutions for the identification and authentication of network nodes within the IoD that are based on Trusted Platform Modules (TPMs), Hardware Security Modules (HSMs), and Physically Unclonable Functions (PUFs). Finally, future directions in these relevant research topics are given, stimulating further work.

Highlights

  • In the forthcoming Internet of Drones (IoD) era [1,2], various types of drones, formally referred to as Unmanned Aerial Vehicles (UAVs) or Remotely Piloted Aircrafts (RPAs), will act as flying smart “things” and collaborate with key enabling technologies, such as the Internet of Things (IoT) [3], cloud computing [4], Mobile Edge Computing (MEC) [5], Machine Learning (ML) [6], Blockchain [7], network slicing [8], Software-Defined Networking (SDN) [9], and Fifth Generation (5G) communications [10]

  • The proposed authentication scheme was evaluated using an Radio Frequency (RF)-based dataset from 3000 drones, and the results indicated that this scheme outperformed other ML-based schemes in terms of accuracy

  • As drones will be integrated as flying things in IoD networks, several possibilities for novel applications and services are envisioned in the forthcoming years

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Summary

Introduction

In the forthcoming Internet of Drones (IoD) era [1,2], various types of drones, formally referred to as Unmanned Aerial Vehicles (UAVs) or Remotely Piloted Aircrafts (RPAs), will act as flying smart “things” and collaborate with key enabling technologies, such as the Internet of Things (IoT) [3], cloud computing [4], Mobile Edge Computing (MEC) [5], Machine Learning (ML) [6], Blockchain [7], network slicing [8], Software-Defined Networking (SDN) [9], and Fifth Generation (5G) communications [10]. Based on the IoD, innovative applications are envisioned in the civilian and military domains, including road traffic monitoring, area mapping, the monitoring of critical infrastructure and industrial facilities, surveillance and disaster management, public safety, entertainment, live streaming, and military services [1,2,3] In this context, drones are expected to be deployed in various missions where human intervention is not feasible. The limited energy, computing, and storage resources of drones make them vulnerable to a wide range of invasive, non-invasive, and semi-invasive attacks [11] Typical paradigms of these attacks are eavesdropping, man-in-the-middle attacks, spoofing, tampering, Denial-of-Service (DoS), impersonation/sybil attacks, replay attacks, and forgery attacks.

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