Drone Communication Research Articles

A Proxy Signature-Based Swarm Drone Authentication With Leader Selection in 5G Networks

Drones are imperative for the 5G architecture as a mobile source to expand network coverage and support seamless services, particularly through enabling device-to-device (D2D) communication. Such deployment of drones in D2D settings raises various security threats in drone communication. While the existing D2D communication security standard within the 4G cellular architecture may address some of these issues, the standard includes heavy traffic toward the network core servers. If this security standard is to be adopted in the 5G D2D security services with the same traffic load, it may negatively impact the 5G network performance. Therefore, this paper proposes a lightweight proxy signature-based authentication mechanism for a swarm of drones compatible with the 5G D2D standard mechanisms. This paper proposes a distributed delegation-based authentication mechanism to reduce the traffic overhead toward the 5G core network. In this scheme, the legitimate drones are authorized as proxy delegated signers to perform authentication on behalf of the core network. Furthermore, we propose a mechanism to elect and relocate a new leader relay drone from the existing drone swarm. We implemented the proposed authentication algorithm in the 5G D2D-based communication package over NS-3 while performing the computational calculations on a RaspberryPi3 device to mimic the drone calculation process and delays. The performance of the proposed authentication shows a promising reduction in the authentication time and shows lightweight and reliable compatibility.

Measurement-Based Large Scale Statistical Modeling of Air–to–Air Wireless UAV Channels via Novel Time–Frequency Analysis

Any operation scenario for unmanned aerial vehicles also known as drones in real world requires resilient wireless link to guarantee capacity and performance for users, which can only be achieved by obtaining detailed knowledge about the propagation channel. Thus, this study investigates the large-scale channel propagation statistics for the line of sight air–to–air (A2A) drone communications to estimate the path loss exponent (PLE). We conducted a measurement campaign at 5.8 GHz, using low cost and light weight software defined radio based channel sounder which is developed in this study and then further integrated on commercially available drones. To determine the PLE, frequency-based, time-based and time–frequency based methods are utilized. Accuracy of the proposed method is verified under ideal conditions in a well-isolated anechoic chamber before the actual measurement campaign to verify the performance in a free space path loss environment. The path loss exponent for A2A wireless drone channel is estimated with these verified methods.

Amassing the Security: An Enhanced Authentication Protocol for Drone Communications over 5G Networks

At present, the great progress made by the Internet of Things (IoT) has led to the emergence of the Internet of Drones (IoD). IoD is an extension of the IoT, which is used to control and manipulate drones entering the flight area. Now, the fifth-generation mobile communication technology (5G) has been introduced into the IoD; it can transmit ultra-high-definition data, make the drones respond to ground commands faster and provide more secure data transmission in the IoD. However, because the drones communicate on the public channel, they are vulnerable to security attacks; furthermore, drones can be easily captured by attackers. Therefore, to solve the security problem of the IoD, Hussain et al. recently proposed a three-party authentication protocol in an IoD environment. The protocol is applied to the supervision of smart cities and collects real-time data about the smart city through drones. However, we find that the protocol is vulnerable to drone capture attacks, privileged insider attacks and session key disclosure attacks. Based on the security of the above protocol, we designed an improved protocol. Through informal analysis, we proved that the protocol could resist known security attacks. In addition, we used the real-oracle random model and ProVerif tool to prove the security and effectiveness of the protocol. Finally, through comparison, we conclude that the protocol is secure compared with recent protocols.

Thermally drawn rechargeable battery fiber enables pervasive power

The increasing demand for mobile computing, communications, and robotics presents a growing need for suitable portable power solutions in non-flat customized electronic devices. Fibers as fundamental building blocks of fabrics and 3D-printed objects provide unique opportunities for developing pervasive multidimensional power systems. The characteristic small diameter (<10−3 m) and high aspect ratios (>106) of fibers and expansion of fibers into 2D and 3D power systems necessitate ultra-long lengths to meet the energy specifications of portable electronic systems. Here, we present a Li-ion battery fiber, fabricated for the first time using a thermal drawing method which occurs with simultaneous flows of multiple complex electroactive gels, particles, and polymers within protective flexible cladding. This top-down approach allows for the production of fully-functional and arbitrarily long lithium-ion fiber batteries. The continuous 140 m fiber battery demonstrates a discharge capacity of ∼123 mAh and discharge energy of ∼217 mWh. The scalability and material tunability of these fibers position them for use in varied non-planar electronic systems, including a 1D-flexible electronic fiber, a 2D-large-scale machine woven electronic fabric (∼1.6 m2), and a 3D-printed structural electronic system. The fiber battery satisfies the requirements of portable electronics systems as it is machine washable, flexible, usable underwater, and fire/rupture-safe. We have demonstrated the powering of a submarine drone, LiFi fabric, and flying drone communication through different rechargeable fiber battery schemes, which paves the way for the emergence of the pervasive battery-powered electronics.

TC-PSLAP: Temporal Credential-Based Provably Secure and Lightweight Authentication Protocol for IoT-Enabled Drone Environments

In smart cities, common infrastructures are merged and integrated with various components of information communication and technology (ICT) to be coordinated and controlled. Drones (unmanned aerial vehicles) are amongst those components, and when coordinated with each other and with the environment, the drones form an Internet of Drones (IoD). The IoD provides real-time data to the users in smart cities by utilizing traditional cellular networks. However, the delicate data gathered by drones are subject to many security threats and give rise to numerous privacy and security issues. A robust and secure authentication scheme is required to allow drones and users to authenticate and establish a session key. In this article, we proposed a provably secure symmetric-key and temporal credential-based lightweight authentication protocol (TC-PSLAP) to secure the drone communication. We prove that the proposed scheme is provably secure formally through the automated verification tool AVISPA and Burrows–Abadi–Needham logic (BAN logic). Informal security analysis is also performed to depict that the proposed TC-PSLAP can resist known attacks.

Uplink and Downlink Variation in Drone Technology for Cloud, Edge, Fog and Smart Dust Integrated IoT Architecture: Demonstrated Over WSNs

IoT concepts are heavily applicable in drone communication integrated with different network architecture for optimization. Distributing the burden allows more IoT devices to execute calculations, rather than everything being done on the cloud. There are numerous IoT designs that have emerged as a result of this. By relocating calculations away from the cloud, these designs make use of the enhanced processing capacity of the devices. Based on our needs, we’ve limited it down to four architectures, each of which we have discussed for optimized flow useful in drone technology. We have also applied the one live dataset for the test drone using raspberry pi processor system powered with for end-to-end drone communication establishment. The analysis of downlink and uplink were studied for time analysis for IoT architecture using drone cell characteristics. New technology makes it possible to implement drone cell (DC) connectivity, which is highly flexible and cost-effective for the gathering of Internet-of-things (IoT) data when terrestrial networks are not yet accessible. DC’s flight path has a substantial impact on data collecting systems.

Cooperative Drone Communications for Space-Air-Ground Integrated Networks

This article explores cooperative communications for drone swarms which become an essential part of space-air-ground integrated networks (SAGINs), since drones (also called unmanned aerial vehicles) have the advantage of fast and flexible deployment. However, the rapid spread of drone applications leads to a dramatic increase in the spectrum and energy demand for drone communications, resulting in a shortage of spectrum and energy resources. Moreover, the inherent broadcast nature of radio propagation makes the air interface of drone communications extremely vulnerable to jamming and eavesdropping attacks, especially considering the fact that an unknown drone may sneak into a swarm for the purpose of intentionally interfering with or tapping confidential transmissions of the legitimate drones. As a consequence, a cooperative networking architecture is proposed for drone-swarm-aided SAGINs. A heterogeneous spectrum sharing mechanism is presented for drone communications to alleviate the spectrum shortage by dynamically identifying and accessing idle spectrum resources with the aid of spectrum sensing and inference. Physical-layer security is also examined for cooperative drone communications with limited energy supply. Finally, a wide range of potential applications of drone communications are pointed out, including emergency wireless networks, beyond 5G and 6G systems, and smart grid.

Research efficiency use of orthogonal double polarization MIMO antennas in drone communication

The article considers possible variants of application of various MIMO schemes for the communication with the drone or unmanned aerial vehicle. The model of multipath propagation of radio waves taking into account polarization parameters of antennas is given. The main focus is on the use of MIMO technology with polarization-orthogonal channels and channels with double polarization. The evaluation of the efficiency of using full polarization reception in comparison with MIMO channels of one polarization is given. Attention is paid to the presence of cross-polarization solution between the channels.

Mobile Network Performance and Technical Feasibility of LTE-Powered Unmanned Aerial Vehicle.

Conventional and license-free radio-controlled drone activities are limited to a line-of-sight (LoS) operational range. One of the alternatives to operate the drones beyond the visual line-of-sight (BVLoS) range is replacing the drone wireless communications system from the conventional industrial, scientific, and medical (ISM) radio band to a licensed cellular-connected system. The Long Term Evolution (LTE) technology that has been established for the terrestrial area allows command-and-control and payload communications between drone and ground station in real-time. However, with increasing height above the ground, the radio environment changes, and utilizing terrestrial cellular networks for drone communications may face new challenges. In this regard, this paper aims to develop an LTE-based control system prototype for low altitude small drones and investigate the feasibility and performance of drone cellular connectivity at different altitudes with measuring parameters such as latency, handover, and signal strength. The measurement results have shown that by increasing flight height from ground to 170 m the received signal power and the signal quality levels were reduced by 20 dBm and 10 dB respectively, the downlink data rate decreased to 70%, and latency increased up to 94 ms. It is concluded that although the existing LTE network can provide a minimum requirement for drone cellular connectivity, further improvements are still needed to enhance aerial coverage, eliminate interference, and reduce network latency.

Cellular Communication Propagation at Drone around Building Environment with Single Knife Edge at 10 GHz

The drone communication systems used a cellular network for controlling a drone from a long distance. That communication propagations between drone and base station were analyzed. The drone moved at the track around building environment. That environment used variations in building height. The communication propagation around building environment caused diffraction mechanism. Single knife edge method is used for that diffraction mechanism. The frequency of communication used 10 GHz. That frequency was influenced by atmospheric attenuation. This research was using some variations such as height of drone track location, transmitter power, and AMC (Adaptive Modulation Coding). MCS (Modulation Coding Scheme) was used AMC such as QPSK, 16 QAM, and 64 QAM. Some result was obtained at this research consist of LOS and NLOS distance, SNR, MCS probability, and percentage of drone coverage. NLOS propagation was caused by building height. The SNR value become increase when higher at drone position, such as drone was moving at 20 meters with height of flying drone 80 m and transmitter power 30 dBm obtained SNR 38.21 dBm. That SNR is affected AMC, so a higher SNR value increases AMC. The drone’s coverage 100%, with a height of flying drone 80 meters and transmitter power of 30 dBm. That condition showed more increasing coverage percentage than 64.8% for height of flying drone 20 meters and transmitter power 30 dBm. That result showed that more drone height increased of coverage percentage, probability modulation, and SNR value.

Fast, Reliable, and Secure Drone Communication: A Comprehensive Survey

Drone security is currently a major topic of discussion among researchers and industrialists. Although there are multiple applications of drones, if the security challenges are not anticipated and required architectural changes are not made, the upcoming drone applications will not be able to serve their actual purpose. Therefore, in this paper, we present a detailed review of the security-critical drone applications, and security-related challenges in drone communication such as DoS attacks, Man-in-the-middle attacks, De-Authentication attacks, and so on. Furthermore, as part of solution architectures, the use of Blockchain, Software Defined Networks (SDN), Machine Learning, and Fog/Edge computing are discussed as these are the most emerging technologies. Drones are highly resource-constrained devices and therefore it is not possible to deploy heavy security algorithms on board. Blockchain can be used to cryptographically store all the data that is sent to/from the drones, thereby saving it from tampering and eavesdropping. Various ML algorithms can be used to detect malicious drones in the network and to detect safe routes. Additionally, the SDN technology can be used to make the drone network reliable by allowing the controller to keep a close check on data traffic, and fog computing can be used to keep the computation capabilities closer to the drones without overloading them.

Ometanje prebrisavanjem sa diskretnim podopsezima - napredna strategija za sprečavanje dronova korišćenih u zlonamerne svrhe

Malicious drones jamming is a subject of numerous researches in the world. The implemented jamming strategy is different in various cases and each improvement in the analysis, modeling and realization contributes to the jamming procedures originality. In this paper, we have analyzed implementation performances of sweep jamming with discrete subbands. This advanced method allows decreasing the problems caused by drone communication and/or telemetry signals jamming on the undesired disruption of navigation signals (GPS and GLONASS) used for the localization of friendly devices in the drone vicinity. The problem is analyzed on the example of one signal frequency intended for drone communication with its operator. Drones with this specific signal frequency are used relatively rarely, but the obtained results are the most illustrative for practical consideration of the problem. The specificity of this frequency is that it is nearest to the navigation signal frequencies which means that important conclusions made for this frequency are satisfied significantly easier for other frequencies intended for drone communication, video and telemetry signals transmission.

Route Optimization Method of UAV Autonomous Transmission Line Detection Based on Beidou Positioning Service

By using Beidou high-precision positioning technology, drone autonomous flight technology, and drone communication technology, a drone inspection system has been constructed. In order to further improve the work efficiency of UAV inspection on transmission lines, a single-base tower UAV inspection track optimization method based on the filtering method of the sphere unit limit is proposed. With the assistance of precision positioning services, the autonomous drone inspection hovering accuracy can reach an average of 5cm (E-W), 6cm (N-S), and 7cm (H), which meets the requirements of fine line inspections. The method proposed in this paper can further improve the efficiency of UAV fine independent inspection while improving the intelligent level of transmission line inspection.

Emerging Drone Trends for Blockchain-Based 5G Networks: Open Issues and Future Perspectives

Unmanned aerial vehicles, commonly known as drones, are receiving growing research interest due to their ability to carry a multitude of sensors and to connect to mobile networks. They are also able to move freely across the air, which enables the creation of numerous applications that were until now considered impracticable. However, such applications may require high computational resources, reliable connection, and high data transmission rates to accomplish different tasks. Therefore, in this work, first, we discuss 5G communication networks and mobile edge computing (MEC) as promising technologies that can provide several benefits to drone-enabled environments and solve some of the presented issues. We also comment on 5G and MEC approaches, presenting the state of the art and seeking to solve each of the latter issues presented. Afterward, we introduce new security concerns of drone communication networks, given their recent popularity. These concerns are related to the possibility of malicious users taking advantage of this brand new technology, which has made many governments ban drones due to public safety. Next, blockchain technology is brought in as a novel solution to the security issues due to its decentralized nature, making it inherently safe. This article also surveys contributions that make use of each of the technologies mentioned to improve the emerging drone industry. Subsequently, we discuss open issues and future perspectives.

Detection, Identification, and Direction of Arrival Estimation of Drone FHSS Signals With Uniform Linear Antenna Array

Safety, security, and privacy are three critical concerns affiliated with the use of drones in everyday life. Considering their ever-shrinking sizes and capabilities, being aware of drone activities in the vicinity becomes an important surveillance item. Therefore, keeping track of drones and preferably their controllers should be included into the already-existing security measures. In this study, a frequency hopping spread spectrum (FHSS) type drone controller signal detection and emitter direction finding framework is proposed to achieve aforementioned goals. Since drone communications signals generally coexist with other FHSS signals in 2.4 GHz industrial, scientific, and medical (ISM) band, first, a method based on cyclostationarity analysis is proposed to distinguish the drone radio controller signals from other signals utilizing 2.4 GHz ISM band. Then, a variant of short-term Fourier transform is introduced to extract the parameters of detected drone remote controller signals. The correct hopping signals are then aggregated based on the clustered parameters to obtain their combined baseband equivalent signal. Furthermore, the resampling process is applied to reduce the unrelated samples in the spectrum and represent the spectrum with the reconstructed signal, which has a much lower bandwidth than the spread bandwidth. Finally, two different multiple signal classification algorithms are utilized to estimate the direction of the drone controller relative to the receiving system. In order to validate the overall performance of the proposed method, the introduced framework is implemented on hardware platforms and tested under real-world conditions. A uniform linear antenna array is utilized to capture over-the-air signals in hilly terrain suburban environments by considering both line-of-sight and non-line–of-sight cases. Direction estimation performance is presented in a comparative manner and relevant discussions are provided.

Guest Editorial: Blockchain Envisioned Drones: Realizing 5G-Enabled Flying Automation

Nowadays the deployment of drones/UAVs is not just limited to military and defense establishments; they are also widely deployed in geo-dispersed applications (environmental monitoring, rescue operation monitoring, road and traffic surveillance, natural disaster monitoring, soil and crop analysis, and consumer product delivery). Drones have become the instigators and enablers of global mechanization. For example, the influx of precocious drones is recognizable looking at the high angled photography of peculiar landscapes. Likewise, multiple drones coordinate and collaborate with each other to form a web of flying computing resources which can sense, analyze, and transmit data to remote cloud servers and storage spaces. Even more, the popularity of next generation communication technologies has opened a new vertical in the form of 5G-en-abled flying automation using drones. This new dimension for drone communication has attracted the wide attention of the academia, research and industrial communities. 5G-enabled flying automation empowers the astronomically large numbers of connected things in a drone-enabled smart ecosystem to communicate among themselves and thereafter decisively handle the progressively intricate traffic conditions.

Fusion of blockchain and artificial intelligence for secure drone networking underlying 5G communications

AbstractNowadays, the exponential increase in the usage of drones in various realms of societal and military applications necessitates advancements and stability in drone communication. Drones have proven their potential in providing real‐time cost‐efficient solutions for several applications like healthcare, smart grid surveillance, smart city monitoring, and border surveillance. Though it has many security and privacy issues, researchers across the globe have given numerous solutions to protect drone communication from cyber‐attacks. Most of these solutions were based on cryptographic techniques and are highly compute extensive. There exist few blockchain‐based solutions, which suffer from high transaction storage costs with communication reliability, latency, and bandwidth issues. Motivated by these facts, in this paper, we present a comprehensive survey to secure drone communication and propose a blockchain‐based secure and intelligent drone communication architecture underlying 5G communication network and artificial intelligence (AI) techniques. The proposed architecture uses an InterPlanetary File System (IPFS) as a platform for data storage, which ensures improved network performance, communication security and privacy, and reduces transaction storage cost. Further, it facilitates efficient drone communication in providing dynamic, flexible, and on‐the‐fly decisions competencies through 5G and AI technologies. Then, we incorporate a healthcare‐based case study using the proposed architecture. At last, future research challenges and directions are emphasized for improvement in this research area.

Blockchain-Based Privacy Preservation for 5G-Enabled Drone Communications

5G-enabled drones have potential applications in a variety of both military and civilian settings (e.g., monitoring and tracking of individuals in demonstrations and/or enforcing of social/ physical distancing during pandemics such as COVID-19). Such applications generally involve the collection and dissemination of (massive) data from the drones to remote data centers for storage and analysis (e.g., via 5G networks). Consequently, there are security and privacy considerations underpinning 5G-enabled drone communications. We posit the potential of leveraging blockchain to facilitate privacy preservation, and therefore in this article we review existing blockchain-based solutions after introducing the architecture for 5G-enabled drone communications and block-chain. We also review existing legislation and data privacy regulations that need to be considered in the design of blockchain-based solutions, as well as identify potential challenges and open issues that will hopefully inform future research.

Secure Key Agreement Protocol for Multi-Drone Communication

Unmanned Aerial Vehicles (UAV), or Drone communication, are developing areas of research that can be used in fields of military, hospital or agriculture. Drone communication keeps up associations among drones and a ground station with a satisfactory information rate for sustaining ongoing transmissions. The communication is imparted between one another through RF. This communication is over the air and it should be encrypted. This guarantees an attacker can't comprehend the caught data. The ongoing research areas focus on efficiently encrypting the channel to make it secure and reducing the dependency on GCS for key generation. This paper proposes a key trade protocol for secure drone to drone communication. Normally in a drone communication, the communication between the Ground Control Station(GCS) and the drones are encrypted utilizing the URANUSLink protocol. The drone to drone communication occurs through the ground station which takes a lot of communication time and resources. Additionally, if an immediate drone to drone communication is built up it is significantly decoded or sets aside the need for effective and secure key generation functions. To overcome the previously mentioned issue the proposed protocol defeats the computation and storage issues by utilizing parameters like Drone ID(DID), Mission ID(MID), Timestamp and Nonce alongside hashing capacities for the key age and communication process. The proposed protocol consists of three phases: i)Registration- the new drones are assigned with DID and MID after registering with the GCS ii)Group-Key Generation- the key is generated using hash functions and iii) Communication Establishment- the keys are exchanged and verified before the communication starts. This protocol guarantees forward secrecy, reverse secrecy and insurance from attacks like eavesdropping, spoofing, replay, and physical capture attacks. AVISPA is utilized for the security examination of the protocol.

A secure authentication scheme framework for mobile-sinks used in the Internet of Drones applications

Within the last decade, communication technologies have evolved rapidly, and this caused significant advancements for Internet of Things (IoT) applications and services. Unmanned aerial vehicles (UAVs), popularly known as drones, has attracted the interest of researches because of their fundamental attributes such as mobility, flexibility, reliability and energy efficiency in wireless networks. Similar to wireless sensor networks (WSNs) and other remote sensing applications, these devices are generally not designed with integrated security mechanisms. Furthermore, the existing solutions in which the main focus is on drone communication security are quite limited in the literature. Since the UAVs have the potential to handle very sensitive data, the exchange of information over wireless channels can cause serious exposures. The authentication schemes to be employed should be handled with care because of the limited resources and energy available with the sensor nodes. The existing enabling UAV technologies have restricted authentication privileges for their interaction with WSNs. In this paper, UAVs which can act like mobile-sinks are considered and existing work on WSN-UAV environment authentication is extended. A secure authentication framework using elliptic-curve crypto-systems is presented. The proposed framework is evaluated to ensure it is resilient to significant well-known potential attacks related with data confidentiality, mutual authentication, password guessing, and key impersonation.