Applications, Deployments, and Integration of Internet of Drones (IoD): A Review

Abualigah, Laith; Diabat, Ali; Sumari, Putra; Gandomi, Amir H.

doi:10.1109/jsen.2021.3114266

Cited by 214 publications

(61 citation statements)

References 71 publications

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“…For intelligent healthcare and image cloud systems, real-time and resourceconstrained security methods are required, and traditional algorithms cannot meet these requirements. As a result, a slew of new algorithms have arisen, all of which are examined [30]- [32]. Figure 3 presents the main five security principles that take on the encryption purpose.…”

Section: Security Principlesmentioning

confidence: 99%

Techniques of medical image encryption taxonomy

2022

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Medical images are one of the most significant and sensitive data types in computer systems. Sending medical images over the internet necessitates using a robust encryption scheme that is resistant to cryptographic attacks. Confidentiality is the most critical part of the three security objectives for information systems security, namely confidentiality, integrity, and availability. Confidentiality is the most critical aspect for the secure storage and transfer of medical images. In this study, we attempt to classify various encryption methods in order to assist researchers in selecting the optimal strategy for protecting sensitive patient information while transferring medical images without alteration and outline the measures that should be adopted to address challenges and concerns relevant to techniques of medical image encryption.

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Section: Security Principlesmentioning

confidence: 99%

Techniques of medical image encryption taxonomy

2022

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“…New energy systems (i.e., Wind-and Solar-based energy generation methods) are getting local and global awareness because of the growing damage rate of nuclear and fossil power sources [11][12][13]. Mainly, operators for Wind and Solar renewable methods are the environmental advantages (loss of carbon emissions because of the value of energy sources and the efficient utilization of fossil energy), decreased expense venture, fuel variegation, and energy independence developed energy performance (less line losses) as well as the possible development of power characteristic and safety and in some instances, possible grid augmentation deferral due to the likelihood of generation close to needing [14].…”

Section: Introductionmentioning

confidence: 99%

Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques

et al. 2022

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Nowadays, learning-based modeling methods are utilized to build a precise forecast model for renewable power sources. Computational Intelligence (CI) techniques have been recognized as effective methods in generating and optimizing renewable tools. The complexity of this variety of energy depends on its coverage of large sizes of data and parameters, which have to be investigated thoroughly. This paper covered the most resent and important researchers in the domain of renewable problems using the learning-based methods. Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. The performance of the given methods in the literature is assessed by a new taxonomy. This paper focus on conducting comprehensive state-of-the-art methods heading to performance evaluation of the given techniques and discusses vital difficulties and possibilities for extensive research. Based on the results, variations in efficiency, robustness, accuracy values, and generalization capability are the most obvious difficulties for using the learning techniques. In the case of the big dataset, the effectiveness of the learning techniques is significantly better than the other computational methods. However, applying and producing hybrid learning techniques with other optimization methods to develop and optimize the construction of the techniques is optionally indicated. In all cases, hybrid learning methods have better achievement than a single method due to the fact that hybrid methods gain the benefit of two or more techniques for providing an accurate forecast. Therefore, it is suggested to utilize hybrid learning techniques in the future to deal with energy generation problems.

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“…In the forthcoming Internet of Drones (IoD) era [1,2], various types of drones, formally referred to as Unmanned Aerial Vehicles (UAVs) or Remotely Piloted Aircrafts (RPAs), will act as flying smart "things" and collaborate with key enabling technologies, such as the Internet of Things (IoT) [3], cloud computing [4], Mobile Edge Computing (MEC) [5], Machine Learning (ML) [6], Blockchain [7], network slicing [8], Software-Defined Networking (SDN) [9], and Fifth Generation (5G) communications [10]. Drones are small, unmanned, fixed-wing or rotary-wing aircrafts that can be rapidly deployed at high elevation angles for short time periods, allowing for cost-effective, flexible, and ubiquitous wireless connections.…”

Section: Introductionmentioning

confidence: 99%

“…Drones are small, unmanned, fixed-wing or rotary-wing aircrafts that can be rapidly deployed at high elevation angles for short time periods, allowing for cost-effective, flexible, and ubiquitous wireless connections. Based on the IoD, innovative applications are envisioned in the civilian and military domains, including road traffic monitoring, area mapping, the monitoring of critical infrastructure and industrial facilities, surveillance and disaster management, public safety, entertainment, live streaming, and military services [1][2][3]. In this context, drones are expected to be deployed in various missions where human intervention is not feasible.…”

Section: Introductionmentioning

confidence: 99%

A Review on Software-Based and Hardware-Based Authentication Mechanisms for the Internet of Drones

Michailidis

Vouyioukas

2022

Drones

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During the last few years, a wide variety of Internet of Drones (IoD) applications have emerged with numerous heterogeneous aerial and ground network elements interconnected and equipped with advanced sensors, computation resources, and communication units. The evolution of IoD networks presupposes the mitigation of several security and privacy threats. Thus, robust authentication protocols should be implemented in order to attain secure operation within the IoD. However, owing to the inherent features of the IoD and the limitations of Unmanned Aerial Vehicles (UAVs) in terms of energy, computational, and memory resources, designing efficient and lightweight authentication solutions is a non-trivial and complicated process. Recently, the development of authentication mechanisms for the IoD has received unprecedented attention. In this paper, up-to-date research studies on authentication mechanisms for IoD networks are presented. To this end, the adoption of conventional technologies and methods, such as the widely used hash functions, Public Key Infrastructure (PKI), and Elliptic-Curve Cryptography (ECC), is discussed along with emerging technologies, including Mobile Edge Computing (MEC), Machine Learning (ML), and Blockchain. Additionally, this paper provides a review of effective hardware-based solutions for the identification and authentication of network nodes within the IoD that are based on Trusted Platform Modules (TPMs), Hardware Security Modules (HSMs), and Physically Unclonable Functions (PUFs). Finally, future directions in these relevant research topics are given, stimulating further work.

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Applications, Deployments, and Integration of Internet of Drones (IoD): A Review

Cited by 214 publications

References 71 publications

Techniques of medical image encryption taxonomy

Techniques of medical image encryption taxonomy

Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques

A Review on Software-Based and Hardware-Based Authentication Mechanisms for the Internet of Drones

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