Title: Horse herd optimised elliptic curve cryptography for secure data aggregation in WSN

Authors: Maravarman Manoharan; Babu Subramani; Pitchai Ramu

Addresses: Department of Computing Technologies, SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, India ' Department of Computing Technologies, SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, India ' Department of Computer Science and Engineering, B V Raju Institute of Technology, Narsapur, Telangana, 502313, India

Abstract: Data aggregation is a highly effective mechanism for improving the lifetime of wireless sensor networks. The prominent problem in data aggregation is security and communication overhead, which increases extra data transmission. The existing work faces problems of accuracy in data transmission, delay, and privacy. In this work, an efficient secure data aggregation with a clustering approach is performed. At first, the nodes in the sensor network are clustered using an adaptive fuzzy clustering approach. An optimal selection of cluster heads shrinks the energy consumption and maximises the network lifetime. Furthermore, enhanced lattice-based homomorphic encryption is applied to the encrypted data for aggregation. This hybrid horse herd optimised elliptic curve cryptography with an enhanced lattice-based homomorphic approach provides security improvement in data transmission. The simulation of the proposed hybrid horse herd optimised elliptic curve cryptography with an enhanced lattice-based homomorphic approach is implemented using a Python tool, and performance was evaluated using various metrics. While compared with existing schemes, the simulation outcomes indicate a considerably higher throughput of 5,002 bps and an average delay of 98.08 ms.

Keywords: wireless sensor network; WSN; horse herd optimised elliptic curve cryptography; enhanced lattice-based homomorphic; optimal rule-based fuzzy approach; data aggregation.

DOI: 10.1504/IJAHUC.2024.140442

International Journal of Ad Hoc and Ubiquitous Computing, 2024 Vol.46 No.4, pp.231 - 247

Received: 16 Mar 2023
Accepted: 19 Mar 2024
Published online: 09 Aug 2024 *

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