Securing the Edge: CatBoost Classifier Optimized by the Lyrebird Algorithm to Detect Denial of Service Attacks in Internet of Things-Based Wireless Sensor Networks

Securing the Edge: CatBoost Classifier Optimized by the Lyrebird Algorithm to Detect Denial of Service Attacks in Internet of Things-Based Wireless Sensor Networks

The security of Wireless Sensor Networks (WSNs) is of the utmost importance because of their widespread use in various applications. Protecting WSNs from harmful activity is a vital function of intrusion detection systems (IDSs). An innovative approach to WSN intrusion detection (ID) utilizing the C...

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Bibliographic Details
Main Authors: Sennanur Srinivasan Abinayaa, Prakash Arumugam, Divya Bhavani Mohan, Anand Rajendran, Abderezak Lashab, Baoze Wei, Josep M. Guerrero
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Future Internet
Subjects:
wireless sensor networks (WSNs)
intrusion detection (ID)
CatBoost classifier (Cb-C)
lyrebird optimization algorithm (LOA)
WSN-DS dataset
machine learning (ML)
Online Access:https://www.mdpi.com/1999-5903/16/10/381

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https://www.mdpi.com/1999-5903/16/10/381

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