A systematic literature review on Security of Unmanned Aerial Vehicle Systems

Unmanned aerial vehicles (UAVs) are becoming more common, and their operational range is expanding tremendously, making the security aspect of the inquiry essential. This study does a thorough assessment of the literature to determine the most common cyberattacks and the effects they have on UAV assaults on civilian targets. The STRIDE assault paradigm, the challenge they present, and the proper tools for the attack are used to categorize the cyber dangers discussed in this paper. Spoofing and denial of service assaults are the most prevalent types of UAV cyberattacks and have the best results. No attack style demands the employment of a hard-to-reach gadget, indicating that the security environment currently necessitates improvements to UAV use in civilian applications.Comment: 10 Pages, 4 Figure

An Integrated Framework for Sensing Radio Frequency Spectrum Attacks on Medical Delivery Drones

Drone susceptibility to jamming or spoofing attacks of GPS, RF, Wi-Fi, and operator signals presents a danger to future medical delivery systems. A detection framework capable of sensing attacks on drones could provide the capability for active responses. The identification of interference attacks has applicability in medical delivery, disaster zone relief, and FAA enforcement against illegal jamming activities. A gap exists in the literature for solo or swarm-based drones to identify radio frequency spectrum attacks. Any non-delivery specific function, such as attack sensing, added to a drone involves a weight increase and additional complexity; therefore, the value must exceed the disadvantages. Medical delivery, high-value cargo, and disaster zone applications could present a value proposition which overcomes the additional costs. The paper examines types of attacks against drones and describes a framework for designing an attack detection system with active response capabilities for improving the reliability of delivery and other medical applications.Comment: 7 pages, 1 figures, 5 table

Securing a UAV Using Features from an EEG Signal

This thesis focuses on an approach which entails the extraction of Beta component of the EEG (Electroencephalogram) signal of a user and uses his/her EEG beta data to generate a random AES (Advanced Encryption Standard) encryption key. This Key is used to encrypt the communication between the UAVs (Unmanned aerial vehicles) and the ground control station. UAVs have attracted both commercial and military organizations in recent years. The progress in this field has reached significant popularity, and the research has incorporated different areas from the scientific domain. UAV communication became a significant concern when an attack on a Predator UAV occurred in 2009, which allowed the hijackers to get the live video stream. Since a UAVs major function depend on its onboard auto pilot, it is important to harden the system against vulnerabilities. In this thesis, we propose a biometric system to encrypt the UAV communication by generating a key which is derived from Beta component of the EEG signal of a user. We have developed a safety mechanism that gets activated in case the communication of the UAV from the ground control station gets attacked. This system was validated on a commercial UAV under malicious attack conditions during which we implement a procedure where the UAV return safely to an initially deployed "home" position

Comparison of drone recognition methods

It is expected that the use of Unmanned Aerial Vehicles, colloquially known also as drones, will see an important grow in the coming years as more cheaper and capable drones enter the market, making possible their use for recreational and economic purposes. These article discuses the security challenges coming from widespread UAV use, why it is necessary to implement Drone Recognition Methods, states the available existing methods and compares them based on their efficiency

Detection and control of small civilian UAVs

With the increasing proliferation of small civilian Unmanned Aerial Vehicles (UAVs), the threat to critical infrastructure (CI) security and privacy is now widely recognised and must be addressed. These devices are easily available at a low cost, with their usage largely unrestricted allowing users to have no accountability. Further, current implementations of UAVs have little to no security measures applied to their control interfaces. To combat the threat raised by small UAVs, being aware of their presence is required, a task that can be challenging and often requires customised hardware. This thesis aimed to address the threats posed by the Parrot AR Drone v2, by presenting a data link signature detection method which provides the characteristics needed to implement a mitigation method, capable of stopping a UAVs movement and video stream. These methods were developed using an experimental procedure and are packaged as a group of Python scripts. A suitable detection method was developed, capable of detecting and identifying a Parrot AR Drone v2 within WiFi operational range. A successful method of disabling the controls and video of a Parrot AR Drone in the air was implemented, with collection of video and control commands also achieved, for after-the-event reconstruction of the video stream. Real-time video monitoring is achievable, however it is deemed detrimental to the flight stability of the Parrot, reducing the effectiveness of monitoring the behaviour of an unidentified Parrot AR Drone v2. Additionally, implementing a range of mitigations for continued monitoring of Parrot AR Drones proved ineffectual, given that the mitigations applied were found to be non-persistent, with the mitigations reverting after control is returned to the controller. While the ability to actively monitor and manipulate Parrot AR Drones was successful, it was not to the degree believed possible during initial research

A Comprehensive Review of Unmanned Aerial Vehicle Attacks and Neutralization Techniques

Unmanned Aerial Vehicles (UAV) have revolutionized the aircraft industry in this decade. UAVs are now capable of carrying out remote sensing, remote monitoring, courier delivery, and a lot more. A lot of research is happening on making UAVs more robust using energy harvesting techniques to have a better battery lifetime, network performance and to secure against attackers. UAV networks are many times used for unmanned missions. There have been many attacks on civilian, military, and industrial targets that were carried out using remotely controlled or automated UAVs. This continued misuse has led to research in preventing unauthorized UAVs from causing damage to life and property. In this paper, we present a literature review of UAVs, UAV attacks, and their prevention using anti-UAV techniques. We first discuss the different types of UAVs, the regulatory laws for UAV activities, their use cases, recreational, and military UAV incidents. After understanding their operation, various techniques for monitoring and preventing UAV attacks are described along with case studies