Editorial

2 pages, 137 KiB

Open AccessEditorial

Advances in Drone Communications, State-of-the-Art and Architectures

by Vishal Sharma

Drones 2019, 3(1), 21; https://doi.org/10.3390/drones3010021 - 23 Feb 2019

Cited by 20 | Viewed by 7866

Unmanned aerial vehicle (UAV)-enabled networks and drone communications are emerging areas of research with a key focus on attaining high throughput, elongated range, and enhanced coverage over the existing networks [...] Full article

(This article belongs to the Special Issue Advances in Drone Communications, State-of-the-Art and Architectures)

Research

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16 pages, 2277 KiB

Open AccessArticle

An Intrusion Detection System for Drone Swarming Utilizing Timed Probabilistic Automata

by Venkatraman Subbarayalu and Maria Anu Vensuslaus

Drones 2023, 7(4), 248; https://doi.org/10.3390/drones7040248 - 03 Apr 2023

Cited by 7 | Viewed by 2771

Abstract

Unmanned aerial vehicles (UAVs), commonly known as drones, have found extensive applications across diverse sectors, such as agriculture, delivery, surveillance, and military. In recent times, drone swarming has emerged as a novel field of research, which involves multiple drones working in collaboration towards [...] Read more.

Unmanned aerial vehicles (UAVs), commonly known as drones, have found extensive applications across diverse sectors, such as agriculture, delivery, surveillance, and military. In recent times, drone swarming has emerged as a novel field of research, which involves multiple drones working in collaboration towards a shared objective. This innovation holds immense potential in transforming the way we undertake tasks, including military operations, environmental monitoring, and search and rescue missions. However, the emergence of drone swarms also brings new security challenges, as they can be susceptible to hacking and intrusion. To address these concerns, we propose utilizing a timed probabilistic automata (TPA)-based intrusion detection system (IDS) to model the normal behavior of drone swarms and identify any deviations that may indicate an intrusion. This IDS system is particularly efficient and adaptable in detecting different types of attacks in drone swarming. Its ability to adapt to evolving attack patterns and identify zero-day attacks makes it an invaluable tool in protecting drone swarms from malicious attacks. Full article

(This article belongs to the Special Issue Advances in Drone Communications, State-of-the-Art and Architectures)

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24 pages, 26715 KiB

Open AccessArticle

A New Image Encryption Algorithm Based on DNA State Machine for UAV Data Encryption

by Moatsum Alawida, Je Sen Teh and Wafa’ Hamdan Alshoura

Drones 2023, 7(1), 38; https://doi.org/10.3390/drones7010038 - 05 Jan 2023

Cited by 13 | Viewed by 2894

Abstract

Drone-based surveillance has become widespread due to its flexibility and ability to access hazardous areas, particularly in industrial complexes. As digital camera capabilities improve, more visual information can be stored in high-resolution images, resulting in larger image sizes. Therefore, algorithms for encrypting digital [...] Read more.

Drone-based surveillance has become widespread due to its flexibility and ability to access hazardous areas, particularly in industrial complexes. As digital camera capabilities improve, more visual information can be stored in high-resolution images, resulting in larger image sizes. Therefore, algorithms for encrypting digital images sent from drones must be both secure and highly efficient. This paper presents a novel algorithm based on DNA computing and a finite state machine (FSM). DNA and FSM are combined to design a key schedule with high flexibility and statistical randomness. The image encryption algorithm is designed to achieve both confusion and diffusion properties simultaneously. The DNA bases themselves provide diffusion, while the random integers extracted from the DNA bases contribute to confusion. The proposed algorithm underwent a thorough set of statistical analyses to demonstrate its security. Experimental findings show that the proposed algorithm can resist many well-known attacks and encrypt large-sized images at a higher throughput compared to other algorithms. High experimental results for the proposed algorithm include correlation coefficients of 0.0001 and Shannon entropy of 7.999. Overall, the proposed image encryption algorithm meets the requirements for use in drone-based surveillance applications. Full article

(This article belongs to the Special Issue Advances in Drone Communications, State-of-the-Art and Architectures)

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19 pages, 2017 KiB

Open AccessArticle

An Intrusion Detection Model for Drone Communication Network in SDN Environment

by Liang Kou, Shanshuo Ding, Ting Wu, Wei Dong and Yuyu Yin

Drones 2022, 6(11), 342; https://doi.org/10.3390/drones6110342 - 04 Nov 2022

Cited by 14 | Viewed by 3073

Abstract

Drone communication is currently a hot topic of research, and the use of drones can easily set up communication networks in areas with complex terrain or areas subject to disasters and has broad application prospects. One of the many challenges currently facing drone [...] Read more.

Drone communication is currently a hot topic of research, and the use of drones can easily set up communication networks in areas with complex terrain or areas subject to disasters and has broad application prospects. One of the many challenges currently facing drone communication is the communication security issue. Drone communication networks generally use software defined network (SDN) architectures, and SDN controllers can provide reliable data forwarding control for drone communication networks, but they are also highly susceptible to attacks and pose serious security threats to drone networks. In order to solve the security problem, this paper proposes an intrusion detection model that can reach the convergence state quickly. The model consists of a deep auto-encoder (DAE), a convolutional neural network (CNN), and an attention mechanism. DAE is used to reduce the original data dimensionality and improve the training efficiency, CNN is used to extract the data features, the attention mechanism is used to enhance the important features of the data, and finally the traffic is detected and classified. We conduct tests using the InSDN dataset, which is collected from an SDN environment and is able to verify the effectiveness of the model on SDN traffic. The experiments utilize the Tensorflow framework to build a deep learning model structure, which is run on the Jupyter Notebook platform in the Anaconda environment. Compared with the CNN model, the LSTM model, and the CNN+LSTM hybrid model, the accuracy of this model in binary classification experiments is 99.7%, which is about 0.6% higher than other comparison models. The accuracy of the model in the multiclassification experiment is 95.5%, which is about 3% higher than other comparison models. Additionally, it only needs 20 to 30 iterations to converge, which is only one-third of other models. The experiment proves that the model has fast convergence speed and high precision and is an effective detection method. Full article

(This article belongs to the Special Issue Advances in Drone Communications, State-of-the-Art and Architectures)

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20 pages, 4178 KiB

Open AccessEditor’s ChoiceArticle

A Hybrid Communication Scheme for Efficient and Low-Cost Deployment of Future Flying Ad-Hoc Network (FANET)

by Muhammad Asghar Khan, Ijaz Mansoor Qureshi and Fahimullah Khanzada

Drones 2019, 3(1), 16; https://doi.org/10.3390/drones3010016 - 11 Feb 2019

Cited by 98 | Viewed by 18572

Abstract

In recent years, FANET-related research and development has doubled, due to the increased demands of unmanned aerial vehicles (UAVs) in both military and civilian operations. Equipped with more capabilities and unique characteristics, FANET is able to play a vital role in mission-critical applications. [...] Read more.

In recent years, FANET-related research and development has doubled, due to the increased demands of unmanned aerial vehicles (UAVs) in both military and civilian operations. Equipped with more capabilities and unique characteristics, FANET is able to play a vital role in mission-critical applications. However, these distinctive features enforce a series of guidelines to be considered for its efficient deployment. Particularly, the use of FANET for on-time data communication services presents demanding challenges in terms of energy efficiency and quality of service (QoS). Proper use of communication architecture and wireless technology will assist to solve these challenges. Therefore, in this paper, we review different communication architectures, including the existing wireless technologies, in order to provide seamless wireless connectivity. Based on the discussions, we conclude that a multi-layer UAV ad-hoc network is the most suitable architecture for networking a group of heterogeneous UAVs, while Bluetooth 5 (802.15.1) is the most favored option because of its low-cost, low power consumption, and longer transmission range for FANET. However, 802.15.1 has the limitation of a lower data rate as compared to Wi-Fi (802.11). Therefore, we propose a hybrid wireless communication scheme so as to utilize the features of the high data transmission rate of 802.11 and the low-power consumption of 802.15.1. The proposed scheme significantly reduces communication cost and improves the network performance in terms of throughput and delay. Further, simulation results using the Optimized Network Engineering Tool (OPNET) further support the effectiveness of our proposed scheme. Full article

(This article belongs to the Special Issue Advances in Drone Communications, State-of-the-Art and Architectures)

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18 pages, 3820 KiB

Open AccessEditor’s ChoiceArticle

Collaboration of Drone and Internet of Public Safety Things in Smart Cities: An Overview of QoS and Network Performance Optimization

by Saeed H. Alsamhi, Ou Ma, M. Samar Ansari and Sachin Kumar Gupta

Drones 2019, 3(1), 13; https://doi.org/10.3390/drones3010013 - 27 Jan 2019

Cited by 99 | Viewed by 11517

Abstract

This paper studies the network performance of collaboration between the Internet of public safety things (IoPST) and drones. Drones play a vital role in delivering timely and essential wireless communication services for the recovery of services right after a disaster by increasing surge [...] Read more.

This paper studies the network performance of collaboration between the Internet of public safety things (IoPST) and drones. Drones play a vital role in delivering timely and essential wireless communication services for the recovery of services right after a disaster by increasing surge capacity for the purposes of public safety, exploring areas that are difficult to reach, and providing an area of rapid coverage and connectivity. To provide such critical facilities in the case of disasters and for the purposes of public safety, collaboration between drones and IoPST is able to support public safety requirements such as real-time analytics, real-time monitoring, and enhanced decision-making to help smart cities meet their public safety requirements. Therefore, the deployment of drone-based wireless communication can save people and ecosystems by helping public safety organizations face threats and manage crises in an efficient manner. The contribution of this work lies in improving the level of public safety in smart cities through collaborating between smart wearable devices and drone technology. Thus, the collaboration between drones and IoPST devices establishes a public safety network that shows satisfying results in terms of enhancing efficiency and information accuracy. Full article

(This article belongs to the Special Issue Advances in Drone Communications, State-of-the-Art and Architectures)

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23 pages, 22935 KiB

Open AccessArticle

An Efficient Mobility Model for Improving Transmissions in Multi-UAVs Enabled WSNs

by Mohd. Abuzar Sayeed and Rajesh Kumar

Drones 2018, 2(3), 31; https://doi.org/10.3390/drones2030031 - 01 Sep 2018

Cited by 18 | Viewed by 6309

Abstract

Multi-Unmanned Aerial Vehicle (UAV) enabled Wireless Sensor Networks (WSNs) provide a wide range of applications, covering civilian and military expeditions along with geographical navigation, control, and reconnaissance. The coordinated networks formed between the UAVs and the WSNs help in enhancing the issues related [...] Read more.

Multi-Unmanned Aerial Vehicle (UAV) enabled Wireless Sensor Networks (WSNs) provide a wide range of applications, covering civilian and military expeditions along with geographical navigation, control, and reconnaissance. The coordinated networks formed between the UAVs and the WSNs help in enhancing the issues related to quality as well as coverage. The overall coverage issues result in starvation as an effect of long waiting time for the nodes, while forwarding the traffic. The coverage problem can be resolved by an intelligent choice of UAV way-points. Therefore, a specialized UAV mobility model is required which takes into account the topological structure as well as the importance of strategic locations to fix UAV way-points and decide the data transmission paradigm. To resolve this problem, a novel mobility model is proposed, which takes into account the attraction factor for setting up the way-points for UAV movements. The model is capable of deciding between the locations which result in more coverage, increased throughput with lesser number of UAVs employed, as justified by the simulation results and comparative evaluations. Full article

(This article belongs to the Special Issue Advances in Drone Communications, State-of-the-Art and Architectures)

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15 pages, 5674 KiB

Open AccessArticle

Dynamic Routing in Flying Ad-Hoc Networks Using Topology-Based Routing Protocols

by Muhammad Asghar Khan, Inam Ullah Khan, Alamgir Safi and Ijaz Mansoor Quershi

Drones 2018, 2(3), 27; https://doi.org/10.3390/drones2030027 - 14 Aug 2018

Cited by 78 | Viewed by 10595

Abstract

The ever-increasing demand for flexible and portable communications has led to a rapid evolution in networking between unmanned aerial vehicles (UAVs) often referred to as flying ad-hoc networks (FANETs). However, due to the exclusive characteristics of UAVs such as high mobility, frequent topology [...] Read more.

The ever-increasing demand for flexible and portable communications has led to a rapid evolution in networking between unmanned aerial vehicles (UAVs) often referred to as flying ad-hoc networks (FANETs). However, due to the exclusive characteristics of UAVs such as high mobility, frequent topology change and 3D space movement, make routing a challenging task in FANETs. Due to these characteristics, designing new routing protocols for FANETs is quite difficult. In the literature study of FANETs, a variety of traditional ad-hoc networking protocols have been suggested and tested for FANETs to establish an efficient and robust communication among the UAVs. In this context, topology-based routing is considered the most significant approach for solving the routing issues in FANETs. Therefore, in this article we specifically focus on topology-based routing protocols with the aim of improving the efficiency of the network in terms of throughput, end-to-end delay, and network load. We present a brief review of the most important topology-based routing protocols in the context of FANETs. We provide them with their working features for exchanging information, along with the pros and cons of each protocol. Moreover, simulation analyses of some of the topology-based routing protocols are also evaluated in terms of end-to-end delay, throughput and network load the using optimized network engineering tools (OPNET) simulator. Furthermore, this work can be used as a source of reference for researchers and network engineers who seek literature that is relevant to routing in FANETs. Full article

(This article belongs to the Special Issue Advances in Drone Communications, State-of-the-Art and Architectures)

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12 pages, 2082 KiB

Open AccessArticle

A Practical Deployment of a Communication Infrastructure to Support the Employment of Multiple Surveillance Drones Systems

by Maik Basso, Iulisloi Zacarias, Carlos Eduardo Tussi Leite, Haijun Wang and Edison Pignaton de Freitas

Drones 2018, 2(3), 26; https://doi.org/10.3390/drones2030026 - 13 Aug 2018

Cited by 13 | Viewed by 5844

Abstract

In many incidents involving amateur drones (ADr), the big challenge is to quickly deploy a surveillance system that countermeasures the threat and keeps track of the intruders. Depending on the area under concern, launching a single surveillance drone (SDr) to hunt the intruder [...] Read more.

In many incidents involving amateur drones (ADr), the big challenge is to quickly deploy a surveillance system that countermeasures the threat and keeps track of the intruders. Depending on the area under concern, launching a single surveillance drone (SDr) to hunt the intruder is not efficient, but employing multiple ones can cope with the problem. However, in order to make this approach feasible, an easy to use mission setup and control station for multiple SDr is required, which by its turn, requires a communication infrastructure able to handle the connection of multiple SDr among themselves and their ground control and payload visualization station. Concerning this Issue, this paper presents a proposal of a network infrastructure to support the operation of multiple SDr and its practical deployment. This infrastructure extends the existing Micro Air Vehicle Link (MAVLink) protocol to support multiple connections among the SDrs and between them and a ground control station. Encouraging results are obtained, showing the viability of this proposed protocol extension. Full article

(This article belongs to the Special Issue Advances in Drone Communications, State-of-the-Art and Architectures)

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