A Security Review in the UAVNet Era: Threats, Countermeasures, and Gap Analysis

Abstract

Unmanned Aerial Vehicles (UAVs) are becoming one of the main technological supports for commercial applications, embracing many domains ranging from human safety to the medical field, agriculture and environment, multimedia production, and even commercial delivery. This rise in popularity, however, is causing an increasing interest from criminals, making UAVs the target of new attacks. To fully characterize the current UAV cybersecurity landscape, we perform a complete literature review, digging into drone security historic facts and scientific studies on the matter, reviewing specialized articles and scientific papers focusing on cybersecurity threats and gaps in the context of small UAVs in commercial applications. Being a recent research and development area, most of the articles have been published between 2016 and 2020 as a direct consequence of the increase of security concerns and interest in the drone field. Papers in this review deal with UAV cyberthreats and related vulnerabilities, identifying flaws experimented in a lab or describing incidents detected in the field. Communication, sensors, and system misconfigurations are among the most important threat vectors, while sensor spoofing/jamming and malware DoS/control are among the most cited threats. Threat vectors permit depicting a complete overview of the topic and potential countermeasures known to date, with related gap analysis, also accounting for the recent Unmanned Aircraft System evolution toward ad hoc or cloud-based UAV networks. Countermeasures include the adoption of traditional communication encryption and standard protocols, GPS spoofing/jamming mitigation, encryption and privacy-aware implementations, and counter-malware techniques, to name the most adopted. It also emerges that often attacks are simply ported or adapted from other attacks in similar domains, while peculiar attacks still remain such as targeted physical attacks, specific UAV malware, and GPS spoofing/jamming.

Understanding and Securing Unmanned Aerial Vehicle (UAV) Services: A Comprehensive Tutorial

“…Another effective approach is to disable unauthorized modifications that could compromise the authenticity of critical UAV components. These measures involve the careful monitoring and control of suppliers and manufacturers to ensure the integrity of the components used in the UAV production [127]. By establishing strict verification procedures and maintaining a transparent supply chain, the organizations can significantly reduce the risk of attacks in the supply chain.…”

GPS Spoofing Attacks in FANETs: A Systematic Literature Review

“…Rugo et al [47] collected ∼125 papers and presented a systematic literature review on drone security. Among these, ∼4 technical papers discussed GPS Spoofing attacks in UAVs.…”

Graphic Neural Network based GPS Spoofing Detection for Cellular-Connected UAV swarm

“…In fact, the cellularconnected UAV swarm is formatted as a Flying Ad-hoc Network (FANET) system that uses an Ad-hoc On-demand Distance Vector (AODV) routing protocol for communication and control. Because the AODV protocol has less protection and authentication on the node, it makes the swarm FANET vulnerable to a spoofing attack [90]. Although the proposed deep learning and transfer learning approaches demonstrate effectiveness in detecting GPS spoofing, they are designed for one single cellular-connected UAV and do not consider the case of a cellular-connected UAV swarm.…”