Work

Trust Aware Water Strider Optimization-Based Clustering with Intrusion Detection in IoT Environments

Year: 2025

Type: article

Abstract: The Internet of Things (IoT) has emerged as a transformative technology revolutionizing domains such as healthcare, smart cities, and e-governance.However, real-time IoT integration faces significant hurdles due to the limited energy resources and computational capabilities of IoT devices.Additionally, security vulnerabilities in IoT systems amplify threats to the integrity and reliability of smart applications, necessitating robust solutions.This study introduces a novel Trust-Aware Improved Water Strider Optimization-based Clustering with Intrusion Detection System (TAIWSOC-IDS) for enhancing IoT environments' security and efficiency.The proposed framework comprises two key stages: clustering and intrusion detection.In the clustering stage, the TAIWSOC technique identifies clusters and cluster heads (CHs) by optimizing a fitness function that considers residual energy, communication distance, and trust metrics, ensuring balanced energy consumption and secure communication.In the intrusion detection stage, a Chaos Game Optimization (CGO)-enhanced Multihead Attention Bidirectional Long Short-Term Memory (MHA-BiLSTM) model is employed.The CGO algorithm optimally tunes the hyper parameters of the MHA-BiLSTM model, improving its ability to accurately classify normal and malicious activities.Experimental evaluation demonstrates that the TAIWSOC-IDS outperforms existing state-of-the-art methods in terms of energy efficiency, clustering reliability, and intrusion detection accuracy.The proposed system achieves enhanced detection rates while significantly reducing false positives, proving its efficacy in mitigating security threats.By addressing both energy efficiency and security concerns, TAIWSOC-IDS serves as a comprehensive framework for developing secure, sustainable, and efficient IoT applications across diverse real-time scenarios.

Source: Tehnicki vjesnik - Technical Gazette

DOI: 10.17559/tv-20250108002248

Authors: Alzaben, Nada, Maashi, Mashael, Alshammeri, Menwa, Saraswathi, V., Buri, R. Kiruba, Priya, S. Gayathri

Institutions: Princess Nourah bint Abdulrahman University, King Saud University, Jouf University, R.M.D. Engineering College

Language: English

Topic: Security in Wireless Sensor Networks

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $431