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A Lightweight Aggregate Authentication Protocol for Internet of Drones | IEEE Conference Publication | IEEE Xplore

A Lightweight Aggregate Authentication Protocol for Internet of Drones


Abstract:

The Internet of Drones (IoD), an innovative aerial-ground communication architecture, has quickly became the driving force for various civilian applications (e.g., body t...Show More

Abstract:

The Internet of Drones (IoD), an innovative aerial-ground communication architecture, has quickly became the driving force for various civilian applications (e.g., body temperature detecting drones during the global pandemic of coronavirus disease). In the IoD, a fleet of drones are deployed over an area of interest, collect task-specific data, and then deliver them to the ground station for further data exploration and analysis. To fully exploit the potential of IoD in today's dynamic and evolving cyber-threat environment, the security and efficiency challenges existing in the IoD communications should be well addressed. Some researchers have developed security mechanisms to enable the authentication between the ground station and the drones in the IoD systems. Nonetheless, those schemes mainly focus on the security aspect but overlook the importance of communication efficiency to the resource-constrained drones. In order to fill this research gap, this paper proposes a lightweight aggregate authentication scheme (hereafter referred to as liteAGAP) to tackle the challenges of communication security and efficiency together. Specifically, liteAGAP utilizes cryptographic primitives such as physical unclonable function and bilinear pairing to efficiently secure the data exchange between the ground station and a group of drones in the IoD systems. To evaluate its security performance, liteAGAP is first implemented in the security-sensitive protocol modeling language. Then, we analyze and verify liteAGAP using AVISPA, which is a well-known Internet security protocol verification framework. We also implement liteAGAP and its counterpart schemes in a simulation environment, where the simulation-based experiments are conducted to obtain the results of communication overhead, running time, memory storage usage, and energy consumption. According to the results of security verification/analysis and performance evaluation, we conclude that not only liteAGAP meets the expected s...
Date of Conference: 06-09 January 2024
Date Added to IEEE Xplore: 18 March 2024
ISBN Information:

ISSN Information:

Conference Location: Las Vegas, NV, USA
References is not available for this document.

I. Tntroduction

The Internet of Things (IoT) applications normally consist of a set of immobile sensors, which are connected to the back-end data collection server via wired/wireless communication systems [1]. In recent years, drones have begun to efficiently replace connected sensors “at rest” with one device that is moveable within different environments, adequate to equip various sensors/devices, adaptable to diverse tasks, and intelligent to collect data on anything, anytime, and anywhere [2]. Inspired by the idea of IoT, there has been a constant effort to keep the momentum forward on the ubiquitous computing and bring forth an innovative aerial-ground communication architecture, which is termed the Internet of Drones (IoD) [3]. As drones are being integrated with other technologies (e.g., artificial intelligence), we will see more IoD systems/applications performing critical missions/tasks, especially where it is costly, risky or impractical for humans to perform [4]. In these scenarios, drones are able to complete missions/tasks in a more efficient and less risky manner [5]. In comparison with vehicular networks [6], where the road infrastructure restricts the movement of vehicles, the IoD drones are provided with more movement flexibility while executing missions/tasks in various areas of interest. Additionally, with the assistance of drones, a considerable amount of manpower can be released and the road traffic can be shifted to the airspace (i.e., thermal imaging and disinfecting drones for COVID-19 [7]), resulting in the improvement of transportation congestion and safety.

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1.
C. Pu and K. Choo, "Lightweight Sybil Attack Detection in IoT based on Bloom Filter and Physical Unclonable Function", Elsevier Computers & Security, vol. 113, pp. 102541, 2022.
2.
C. Pu, I. Ahmed, E. Allen and K. Choo, "A Stochastic Packet Forwarding Algorithm in Flying Ad Hoc Networks: Design Analysis and Evaluation", IEEE Access, vol. 9, pp. 162614-162632, 2021.
3.
S. Krishnan and M. Murugappan, Internet of Drones: Applications Opportunities and Challenges, CRC Press, 2023.
4.
C. Pu, "A Reinforcement Learning Based Service Scheduling Algorithm for Internet of Drones", Proc. IEEE ICC Workshops, pp. 999-1004, 2022.
5.
C. Pu and L. Carpenter, "To Route or To Ferry: A Hybrid Packet Forwarding Algorithm in Flying Ad Hoc Networks", Proc. IEEE NCA, pp. 1-8, 2019.
6.
C. Pu, "A novel blockchain-based trust management scheme for vehicular networks", Proc. IEEE WTS, pp. 1-6, 2021.
7.
M. Pathak, D. Dwivedi, N. Kaur, V. Chaturvedi, A. Dwivedi, R. Singh, et al., Application of Cognitive Internet of Things (IoT) for COVID-19 Pandemic, Chapman and Hall/CRC, 2022.
8.
C. Pu and L. Carpenter, "Psched: A Priority-Based Service Scheduling Scheme for the Internet of Drones", IEEE Systems Journal, vol. 15, no. 3, pp. 4230-4239, 2020.
9.
C. Pu, A. Wall, K. Choo, I. Ahmed and S. Lim, "A Lightweight and Privacy-Preserving Mutual Authentication and Key Agreement Protocol for Internet of Drones Environment", IEEE Internet Things J., vol. 9, no. 12, pp. 9918-9933, 2022.
10.
G. Zhu, J. Xu, K. Huang and S. Cui, "Over-the-Air Computing for Wireless Data Aggregation in Massive IoT", IEEE Wireless Communications, vol. 28, no. 4, pp. 57-65, 2021.
11.
J. Wang, L. Wu, S. Zeadally, M. Khan and D. He, "Privacy-preserving Data Aggregation against Malicious Data Mining Attack for IoT-enabled Smart Grid", ACM Transactions on Sensor Networks, vol. 17, no. 3, pp. 1-25, 2021.
12.
A. Ullah, M. Azeem, H. Ashraf, A. Alaboudi, M. Humayun and N. Jhanjhi, "Secure Healthcare Data Aggregation and Transmission in IoT-A Survey", IEEE Access, vol. 9, pp. 16849-16865, 2021.
13.
A. Berini, M. Ferrag, B. Farou and H. Seridi, "HCALA: Hyperelliptic curve-based anonymous lightweight authentication scheme for Internet of Drones", Pervasive and Mobile Computing, vol. 92, pp. 101798, 2023.
14.
D. Chaudhary, T. Soni, K. Vasudev and K. Saleem, "A modified lightweight authenticated key agreement protocol for Internet of Drones", Internet of Things, vol. 21, pp. 100669, 2023.
15.
C. Pu, A. Wall, I. Ahmed and K. Choo, "SecureIoD: A Secure Data Collection and Storage Mechanism for Internet of Drones", Proc. IEEE MDM, pp. 83-92, 2022.
16.
Automated Validation of Internet Security Protocols and Applications.
17.
Y. Yang, L. Zhang, Y. Zhao, K. Choo and Y. Zhang, "Privacy-Preserving Aggregation-Authentication Scheme for Safety Warning System in Fog-Cloud Based VANET", IEEE Trans. Inf. Forensics Security, vol. 17, pp. 317-331, 2022.
18.
M. Nakkar, R. AlTawy and A. Youssef, "GASE: A Lightweight Group Authentication Scheme With Key Agreement for Edge Computing Applications", IEEE Internet Things J., vol. 10, no. 1, pp. 840-854, 2023.
19.
Internet-of-Drones: Novel Applications Recent Deployments and Integration.
20.
The sky is not the limit: The past present and future of the Internet of Drones.
21.
G. Bansal and B. Sikdar, "S-MAPS: Scalable Mutual Authentication Protocol for Dynamic UAV Swarms", IEEE Transactions on Vehicular Technology, vol. 70, no. 11, pp. 12088-12100, 2021.
22.
S. Hussain, S. Chaudhry, O. Alomari, M. Alsharif, M. Khan and N. Kumar, "Amassing the Security: An ECC-Based Authentication Scheme for Internet of Drones", IEEE Systems Journal, vol. 15, no. 3, pp. 4431-4438, 2021.
23.
A. Yazdinejadna, R. Parizi, A. Dehghantanha and H. Karimipour, "Federated learning for drone authentication", Ad Hoc Networks, vol. 120, pp. 102574, 2021.
24.
Y. Aydin, G. Kurt, E. Ozdemir and H. Yanikomeroglu, "Group Authentication for Drone Swarms", Proc. IEEE WiSEE, pp. 72-77, 2021.
25.
M. Abdel-Malek, K. Akkaya, A. Bhuyan and A. Ibrahim, "A Proxy Signature-Based Drone Authentication in 5G D2D Networks", Proc. IEEE VTC2021-Spring, pp. 1-7, 2021.
26.
C. Lai and Z. Chen, "Group-based Handover Authentication for Space-Air-Ground Integrated Vehicular Networks", Proc. IEEE ICC, pp. 1-6, 2021.
27.
Y. Tan, J. Wang, J. Liu and N. Kato, "Blockchain-Assisted Distributed and Lightweight Authentication Service for Industrial Unmanned Aerial Vehicles", IEEE Internet Things J., vol. 9, no. 18, pp. 16928-16940, 2022.
28.
M. El-Zawawy, A. Brighente and M. Conti, "SETCAP: Service-Based Energy-Efficient Temporal Credential Authentication Protocol for Internet of Drones", Computer Networks, vol. 206, pp. 108804, 2022.
29.
How Police Drones Technology Can Be Used at a Protest.
30.
Q. Do, B. Martini and K. Choo, "The role of the adversary model in applied security research", Computers & Security, vol. 81, pp. 156-181, 2019.

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