Big data analytics for large‐scale UAV‐MBN in quantum networks using efficient hybrid GKM

R, Mahaveerakannan and C, Suresh Gnana Dhas (2022) Big data analytics for large‐scale UAV‐MBN in quantum networks using efficient hybrid GKM. Concurrency and Computation: Practice and Experience, 34 (7). ISSN 1532-0626

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Abstract

Summary

A primary important aspect of wireless network domain is known to be secured communication as the signals are emphatically available and broadcasted through the air. Quantum wireless networks are a hot topic of research in recent years that made researchers to avail new techniques in this field. Big data is one of the major aspects that support large‐scale quantum network applications. As sensor nodes have resource constraints, it is more complex when using the traditional techniques of key establishment that only used for stable communication networks. Group‐related applications are also one of the important aspects in wireless network for sending and receiving messages from multiple users. Unfortunately, maintenance of security for the group‐oriented protocols is major issue due to the frequent changes in membership. In this paper, a hybrid GKM with re‐keying procedure is proposed to obtain a secure communication for the remote system of unmanned autonomous vehicle (UAV) with mobile backbone network (MBN). Here, the group controller is selected based on the simplified hybrid energy efficient distributed (HEED) protocol and honey key encryption algorithm is used by the key management center (KMC) for generating and distribution of key for the group's controller. The secure communication is explored using the key exchange mechanism between the nodes. The joining and leaving of a node from the group are initiated by the re‐keying process. The simulation results explain the improved performance of the proposed hybrid method when compared with other existing techniques in terms of privacy level, energy, memory, and time consumption.

Item Type: Article
Subjects: Computer Science and Engineering > Network security
Divisions: Computer Science and Engineering
Depositing User: Unnamed user with email techsupport@mosys.org
Date Deposited: 31 Oct 2026 11:42
Last Modified: 31 Oct 2026 11:42
URI: https://ir.vcenggw.ac.in/id/eprint/683

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