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

Malicious Digital Penetration of United States Weaponized Military Unmanned Aerial Vehicle Systems: A National Security Perspective Concerning the Complexity of Military UAVs and Hacking

The United States’ (US) military unmanned aerial vehicle (UAV) has seen increased usage under the post 9/11 military engagements in the Middle East, Afghanistan, and within American borders. However, the very digital networks controlling these aircrafts are now enduring malicious intrusions (hacking) by America’s enemies. . The digital intrusions serve as a presage over the very digital networks the US relies upon to safeguard its national security and interests and domestic territory. The complexity surrounding the hacking of US military UAVs appears to be increasing, given the advancements in digital networks and the seemingly inauspicious nature of artificial intelligence and autonomous systems. Being most victimized by malicious digital intrusions, the US continues its military components towards growing dependence upon digital networks in advancing warfare and national security and interests. Thus, America’s netcentric warfare perspectives may perpetuate a chaotic environment where the use of military force is the sole means of safeguarding its digital networks

A Secure Real-time Multimedia Streaming through Robust and Lightweight AES Encryption in UAV Networks for Operational Scenarios in Military Domain

multimodal data encryption and decryption for security applications in protected environments like espionage, situational awareness, monitoring, and counter-UAV. Data is captured from drones equipped with microphone arrays and cameras. This is performed by exploiting acoustic event analysis, video tracking, and recognition, performed on a ground station. All the communications are delivered in a secure data channel. Integrity and secrecy of the sensitive data acquired by drones must be guaranteed until the data is delivered in real-time from UAVs to the destination node. A possible data exploit may cause critical problems if the data is intercepted by malicious attackers. Being the drones equipped with low energy consuming devices with low computational power, like single-board-computers, a real-time lightweight application-level AES encryption, in addition to the MAC encryption of the wireless communication channel, has been considered. In the experiment, the encryption and decryption process has been optimized, even under adverse transmission conditions ensuring continuous data encryption even if some packets are lost or the connection is repeatedly dropped and reestablished

Verification of Localization via Blockchain Technology on Unmanned Aerial Vehicle Swarm

Verification of the geographic location of a moving device is vital. This verification is important in terms of ensuring that the flying systems moving in the swarm are in orbit and that they are able to task completion and manage their energy efficiency. Cyber-attacks on unmanned aerial vehicles (UAV) in a swarm can affect their position and cause various damages. In order to avoid this challenge, it is necessary to share with each other the positions of UAV in the swarm and to increase their accuracy. In this study, it is aimed to increase position accuracy and data integrity of UAV by using blockchain technology in swarm. Experiments were conducted on a virtual UAV network (UAVNet). Successful results were obtained from this proposed study

Cyber Risk Assessment and Scoring Model for Small Unmanned Aerial Vehicles

The commercial-off-the-shelf small Unmanned Aerial Vehicle (UAV) market is expanding rapidly in response to interest from hobbyists, commercial businesses, and military operators. The core commercial mission set directly relates to many current military requirements and strategies, with a priority on short range, low cost, real time aerial imaging, and limited modular payloads. These small vehicles present small radar cross sections, low heat signatures, and carry a variety of sensors and payloads. As with many new technologies, security seems secondary to the goal of reaching the market as soon as innovation is viable. Research indicates a growth in exploits and vulnerabilities applicable to small UAV systems, from individual UAV guidance and autopilot controls to the mobile ground station devices that may be as simple as a cellphone application controlling several aircraft. Even if developers strive to improve the security of small UAVs, consumers are left without meaningful insight into the hardware and software protections installed when buying these systems. To date, there is no marketed or accredited risk index for small UAVs. Building from similar domains of aircraft operation, information technologies, cyber-physical systems, and cyber insurance, a cyber risk assessment methodology tailored for small UAVs is proposed and presented in this research. Through case studies of popular models and tailored mission-environment scenarios, the assessment is shown to meet the three objectives of ease-of-use, breadth, and readability. By allowing a cyber risk assessment at or before acquisition, organizations and individuals will be able to accurately compare and choose the best aircraft for their mission

Onboard Audio and Video Processing for Secure Detection, Localization, and Tracking in Counter-UAV Applications

Nowadays, UAVs are of fundamental importance in numerous civil applications like search and rescue and military applications like monitoring and patrolling or counter-UAV where the remote UAV nodes collect sensor data. In the last case, flying UAVs collect environmental data to be used to contrast external attacks launched by adversary drones. However, due to the limited computing resources on board of the acquisition UAVs, most of the signal processing is still performed on a ground central unit where the sensor data is sent wirelessly. This poses serious security problems from malicious entities such as cyber attacks that exploit vulnerabilities at the application level. One possibility to reduce the risk is to concentrate part of the computing onboard of the remote nodes. In this context, we propose a framework where detection of nearby drones and their localization and tracking can be performed in real-time on the small computing devices mounted on board of the drones. Background subtraction is applied to the video frames for pre-processing with the objective of an on-board UAV detection using machine-vision algorithms. For the localization and tracking of the detected UAV, multi-channel acoustic signals are instead considered and DOA estimations are obtained through the MUSIC algorithm. In this work, the proposed idea is described in detail along with some experiments and, then, methods of effective implementation are provided