Security, privacy and safety evaluation of dynamic and static fleets of drones

Abstract

Abstract-Interconnected everyday objects, either via public or private networks, are gradually becoming reality in modern life -often referred to as the Internet of Things (IoT) or Cyber-Physical Systems (CPS). One stand-out example are those systems based on Unmanned Aerial Vehicles (UAVs). Fleets of such vehicles (drones) are prophesied to assume multiple roles from mundane to high-sensitive applications, such as prompt pizza or shopping deliveries to the home, or to deployment on battlefields for battlefield and combat missions. Drones, which we refer to as UAVs in this paper, can operate either individually (solo missions) or as part of a fleet (group missions), with and without constant connection with a base station. The base station acts as the command centre to manage the drones' activities; however, an independent, localised and effective fleet control is necessary, potentially based on swarm intelligence, for several reasons: 1) an increase in the number of drone fleets; 2) fleet size might reach tens of UAVs; 3) making time-critical decisions by such fleets in the wild; 4) potential communication congestion and latency; and 5) in some cases, working in challenging terrains that hinders or mandates limited communication with a control centre, e.g. operations spanning long period of times or military usage of fleets in enemy territory. This self-aware, mission-focused and independent fleet of drones may utilise swarm intelligence for a), air-traffic or flight control management, b) obstacle avoidance, c) self-preservation (while maintaining the mission criteria), d) autonomous collaboration with other fleets in the wild, and e) assuring the security, privacy and safety of physical (drones itself) and virtual (data, software) assets. In this paper, we investigate the challenges faced by fleet of drones and propose a potential course of action on how to overcome them.

Routing and collision avoidance techniques for unmanned aerial vehicles: Analysis, optimal solutions, and future directions

“…To enhance security, a drone delivery system network interdiction‐based mathematical framework was proposed. Preventive infrastructure maintenance of 5G and energy transmission was proposed in Zahariadis et al 145 To maintain a large number of localized UAVs, effective control methods were proposed in Akram et al 146 …”

A Swarm-Based Approach to Generate Challenging Mazes

“…In [ 43 ], swarm intelligence has been proposed for the management of autonomous and independent unmanned aerial vehicles (drones). The challenges faced by fleet of drones during all operations ranging from flight control to cybersecurity are investigated.…”

Intelligent Cyber-Security System for IoT-Aided Drones Using Voting Classifier

“…In recent times, another emerging field of research has been the attempt to make drones smart by adding a few sensors that a small drone may be sufficiently capable of carrying. A set of devices such as sensors, transmitters, and cameras for many different and complex applications can make drones more useful and effective [14].…”