Title: Intrusion detection and optimal path-based energy efficient data transmission using MLVQ and BM-MSOA in MANET

Authors: R. Venketesh; K. Sasikala

Addresses: Department of Computer Science, VMKV Engineering College, Salem, Vinayaka Mission Research Foundation (VMRF), Salem, Tamil Nadu, 636308, India ' Department of Information Technology, RP Sarathy Institute of Technology, Poosaripatty Village, Omalur Taluk, Salem – 636305, Tamil Nadu, India; Anna University, Chennai, Tamil Nadu, India

Abstract: In the wireless network, the MANET is a core technology that offers multi-hop communications between the source node (SN) and destination node (DN). The MANETs are susceptible to diverse security attacks due to the broadcast behaviour of transmission, restricted computation ability, and increasing application areas. Thus, intrusion detection is needed to handle these security issues. Thus, this work develops an efficient intrusion detection system (IDS) in MANET utilising MLVQ neural network (NN). The proposed system offers energy-efficient data transmission (DT) by sending data via the optimal path. Then, the MLVQ NN detects the attacked data and normal data in the intrusion detection phase. The data are isolated and stored in a log file. Later, the optimal path is chosen by BM-MSOA centred on the MN residual energy and path distance. The proposed methodology detects the intrusion with higher accuracy and minimal energy consumption (EC) compared with the prevailing techniques.

Keywords: mobile ad hoc network; MANET; mobile nodes; MN; intrusion detection; energy efficient data transmission; modified learning vector quantisation; MLVQ; Brownian motion based modified sunflower optimisation algorithm; BM-MSOA.

DOI: 10.1504/IJCCBS.2024.146786

International Journal of Critical Computer-Based Systems, 2024 Vol.11 No.4, pp.255 - 279

Received: 31 May 2023
Accepted: 10 Aug 2023
Published online: 17 Jun 2025 *

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