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Article

Anonymous Mutual and Batch Authentication with Location Privacy of UAV in FANET

1
Department of ECE, GMR Institute of Technology, Rajam, Srikakulam 532127, Andhra Pradesh, India
2
Artificial Intelligence Engineering Department, Research Center for AI and IoT, AI and Robotics Institute, Near East University, Mersin 10, Turkey
3
University of Waterloo, Waterloo, ON N2L 3G1, Canada
4
Computer Science Department, University of Camerino, 62032 Camerino, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Vishal Sharma
Drones 2022, 6(1), 14; https://doi.org/10.3390/drones6010014
Received: 13 December 2021 / Revised: 5 January 2022 / Accepted: 5 January 2022 / Published: 7 January 2022
As there has been an advancement in avionic systems in recent years, the enactment of unmanned aerial vehicles (UAV) has upgraded. As compared to a single UAV system, multiple UAV systems can perform operations more inexpensively and efficiently. As a result, new technologies between user/control station and UAVs have been developed. FANET (Flying Ad-Hoc Network) is a subset of the MANET (Mobile Ad-Hoc Network) that includes UAVs. UAVs, simply called drones, are used for collecting sensitive data in real time. The security and privacy of these data are of priority importance. Therefore, to overcome the privacy and security threats problem and to make communication between the UAV and the user effective, a competent anonymous mutual authentication scheme is proposed in this work. There are several methodologies addressed in this work such as anonymous batch authentication in FANET which helps to authenticate a large group of drones at the same time, thus reducing the computational overhead. In addition, the integrity preservation technique helps to avoid message alteration during transmission. Moreover, the security investigation section discusses the resistance of the proposed work against different types of possible attacks. Finally, the proposed work is related to the prevailing schemes in terms of communication and computational cost and proves to be more efficient. View Full-Text
Keywords: authentication; privacy; security; FANET authentication; privacy; security; FANET
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MDPI and ACS Style

Rajasekaran, A.S.; Maria, A.; Al-Turjman, F.; Altrjman, C.; Mostarda, L. Anonymous Mutual and Batch Authentication with Location Privacy of UAV in FANET. Drones 2022, 6, 14. https://doi.org/10.3390/drones6010014

AMA Style

Rajasekaran AS, Maria A, Al-Turjman F, Altrjman C, Mostarda L. Anonymous Mutual and Batch Authentication with Location Privacy of UAV in FANET. Drones. 2022; 6(1):14. https://doi.org/10.3390/drones6010014

Chicago/Turabian Style

Rajasekaran, Arun S., Azees Maria, Fadi Al-Turjman, Chadi Altrjman, and Leonardo Mostarda. 2022. "Anonymous Mutual and Batch Authentication with Location Privacy of UAV in FANET" Drones 6, no. 1: 14. https://doi.org/10.3390/drones6010014

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