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research-article

A survey on recent optimal techniques for securing unmanned aerial vehicles applications

Authors:

Sachin Kumar Gupta,

Saeed Hamood Alsamhi,

Xuan LiuAuthors Info & Claims

Transactions on Emerging Telecommunications Technologies, Volume 32, Issue 7

https://doi.org/10.1002/ett.4133

Published: 05 July 2021 Publication History

Abstract

Unmanned aerial vehicles (UAVs) or Drones technology has a huge potential for supporting different efficient solutions for the smart applications in our world. The applications include smart things, smart transportation, smart cities, smart healthcare, smart personal care, smart house, smart industries, and so on. Due to the sensitive applications of UAVs, the security has become a major concern, and therefore, efficient techniques are required to protect captured data from hackers and the fictitious activities from illegitimate users. Machine learning (ML) techniques play a vital role in improving UAVs' security intelligently, while blockchain is recent technology for decentralized UAVs and security. Furthermore, watermarking guarantees digital media to be authenticated, protected, and copyright. Therefore, we provide a comprehensive survey of optimal techniques, which are used for securing UAVs applications in terms of blockchain, ML, and watermarking. Furthermore, we introduce each technique with the advantages and suitably used for securing UAVs collaboration applications. This survey contributes to a better understanding of the blockchain, ML, and watermarking techniques for securing UAVs and sheds new light on challenges and opportunities on subject applications.

Graphical Abstract

Unmanned aerial vehicles (UAVs) or Drones technology has a huge potential for supporting different efficient solutions for the smart applications in our world. Due to the sensitive applications of UAVs, the security has become a major concern, and therefore, efficient techniques are required to protect captured data from hackers and the fictitious activities from illegitimate users. Therefore, we provide a comprehensive survey of optimal techniques, which are used for securing UAVs applications in terms of blockchain, ML, and watermarking. This survey contributes to a better understanding of the blockchain, ML, and watermarking techniques for securing UAVs and sheds new light on challenges and opportunities on subject applications.

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Cited By

Mohammed AFourati LFakhrudeen A(2024)Comprehensive systematic review of intelligent approaches in UAV-based intrusion detection, blockchain, and network securityComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.110140239:COnline publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1016/j.comnet.2023.110140
Shukla SGupta AGupta P(2024)Exploring the feasibility of adversarial attacks on medical image segmentationMultimedia Tools and Applications10.1007/s11042-023-15575-883:4(11745-11768)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1007/s11042-023-15575-8
Azadur RPawase CChang K(2024)Multi‐UAV path planning utilizing the PGA algorithm for terrestrial IoT sensor network under ISAC frameworkTransactions on Emerging Telecommunications Technologies10.1002/ett.491635:1Online publication date: 15-Jan-2024
https://dl.acm.org/doi/10.1002/ett.4916
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Index Terms

A survey on recent optimal techniques for securing unmanned aerial vehicles applications
1. Security and privacy
2. Social and professional topics
  1. Computing / technology policy
    1. Computer crime

Index terms have been assigned to the content through auto-classification.

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cover image Transactions on Emerging Telecommunications Technologies

Transactions on Emerging Telecommunications Technologies Volume 32, Issue 7

July 2021

405 pages

EISSN:2161-3915

DOI:10.1002/ett.v32.7

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© 2020 John Wiley & Sons, Ltd.

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Published: 05 July 2021

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Cited By

Mohammed AFourati LFakhrudeen A(2024)Comprehensive systematic review of intelligent approaches in UAV-based intrusion detection, blockchain, and network securityComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.110140239:COnline publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1016/j.comnet.2023.110140
Shukla SGupta AGupta P(2024)Exploring the feasibility of adversarial attacks on medical image segmentationMultimedia Tools and Applications10.1007/s11042-023-15575-883:4(11745-11768)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1007/s11042-023-15575-8
Azadur RPawase CChang K(2024)Multi‐UAV path planning utilizing the PGA algorithm for terrestrial IoT sensor network under ISAC frameworkTransactions on Emerging Telecommunications Technologies10.1002/ett.491635:1Online publication date: 15-Jan-2024
https://dl.acm.org/doi/10.1002/ett.4916
Bashir NBoudjit SDauphin G(2023)A Connectivity Aware Path Planning for a Fleet of UAVs in an Urban EnvironmentIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.328099524:10(10537-10552)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1109/TITS.2023.3280995
Omolara AAlawida MAbiodun O(2023)Drone cybersecurity issues, solutions, trend insights and future perspectives: a surveyNeural Computing and Applications10.1007/s00521-023-08857-735:31(23063-23101)Online publication date: 31-Aug-2023
https://dl.acm.org/doi/10.1007/s00521-023-08857-7
Srivastava APrakash J(2022)Internet of Low-Altitude UAVs (IoLoUA): a methodical modeling on integration of Internet of “Things” with “UAV” possibilities and testsArtificial Intelligence Review10.1007/s10462-022-10225-156:3(2279-2324)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1007/s10462-022-10225-1
Alsamhi SAlmalki FAl-Dois HBen Othman SHassan JHawbani ASahal RLee BSaleh H(2021)Machine Learning for Smart Environments in B5G NetworksComputational Intelligence and Neuroscience10.1155/2021/68051512021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/6805151
Khan AGupta SGupta S(2021)Unmanned aerial vehicle‐enabled layered architecture based solution for disaster managementTransactions on Emerging Telecommunications Technologies10.1002/ett.437032:12Online publication date: 8-Dec-2021
https://dl.acm.org/doi/10.1002/ett.4370

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