Open Access

ARTICLE

A Novel MegaBAT Optimized Intelligent Intrusion Detection System in Wireless Sensor Networks

G. Nagalalli^*, G. Ravi

Department of Electronics and Comunication Engineering, Sona College of Technology, Salem, 636005, India

* Corresponding Author: G. Nagalalli. Email:

Intelligent Automation & Soft Computing 2023, 35(1), 475-490. https://doi.org/10.32604/iasc.2023.026571

Received 30 December 2021; Accepted 01 March 2022; Issue published 06 June 2022

Abstract

Wireless Sensor Network (WSN), which finds as one of the major components of modern electronic and wireless systems. A WSN consists of numerous sensor nodes for the discovery of sensor networks to leverage features like data sensing, data processing, and communication. In the field of medical health care, these network plays a very vital role in transmitting highly sensitive data from different geographic regions and collecting this information by the respective network. But the fear of different attacks on health care data typically increases day by day. In a very short period, these attacks may cause adversarial effects to the WSN nodes. Furthermore, the existing Intrusion Detection System (IDS) suffers from the drawbacks of limited resources, low detection rate, and high computational overhead and also increases the false alarm rates in detecting the different attacks. Given the above-mentioned problems, this paper proposes the novel MegaBAT optimized Long Short Term Memory (MBOLT)-IDS for WSNs for the effective detection of different attacks. In the proposed framework, hyperparameters of deep Long Short-Term Memory (LSTM) were optimized by the meta-heuristic megabat algorithm to obtain a low computational overhead and high performance. The experimentations have been carried out using (Wireless Sensor NetworkDetection System)WSN-DS datasets and performance metrics such as accuracy, recall, precision, specificity, and F1-score are calculated and compared with the other existing intelligent IDS. The proposed framework provides outstanding results in detecting the black hole, gray hole, scheduling, flooding attacks and significantly reduces the time complexity, which makes this system suitable for resource-constraint WSNs.

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Keywords

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