title: Customized dataset-based machine learning approach for black hole attack detection in mobile ad hoc networks
abstract: This article explores the application of machine learning (ML) algorithms to classify the black hole attack in mobile ad hoc networks (MANETs). Black hole attacks threaten MANETs by disrupting communication and data transmission. The primary goal of this study is to develop an intrusion detection system (IDS) to detect and classify this attack. The research process involves feature selection, the creation of a custom dataset tailored to the characteristics of black hole attacks, and the evaluati
journal: International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering