Gope, P. and Sikdar, B. (2020) An efficient privacy-preserving authenticated key agreement scheme for edge-assisted internet of drones. IEEE Transactions on Vehicular Technology, 69 (11). pp. 13621-13630. ISSN 0018-9545
Abstract
There has been a a significant increase in the popularity of using Unmanned Aerial Vehicles (UAVs), popularly known as drones, in several applications. In many application scenarios, UAVs are deployed in missions where sensitive data is collected, such as monitoring critical infrastructure, industrial facilities, crops, and public safety. Due to the sensitive and/or safety critical nature of the data collected in these applications, it is imperative to consider the security and privacy aspects of the UAVs used in these scenarios. In this article, we propose an efficient privacy aware authentication scheme for edge-assisted UAVs (Internet of Drones). Unlike the existing security solutions for UAV, our proposed scheme does not require to store any secret key in the devices but still can ensure the desired security level. To the best of our knowledge, this is the first article, where physical security of the UAV has taken into account. The proposed system allows third-party communication and mobile edge computing service provides to authenticate the UAVs without any loss of provacy and outperforms existing methods in terms of computational complexity.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Internet of Drones; Mutual Authentication; Double PUF; Computational Efficiency; Unmanned Aerial Vehicles |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 25 Aug 2020 06:58 |
Last Modified: | 26 Jan 2022 10:42 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/tvt.2020.3018778 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:164796 |