Title: Black hole attacks recognition in wireless mobile ad hoc networks (MANET)

Authors: A. Rajasekar; V. Kavitha; Hima Vijayan; Sheshang Degadwala

Addresses: Department of Artificial Intelligence and Data Science, Sri Sairam Institute of Technology, Sai Leo Nagar, West Tambaram, Chennai, 600044, Tamil Nadu, India ' Department of Artificial Intelligence and Data Science, V.S.B. Engineering College, NH-67, Covai Road, Karudayampalayam Post, Karur, 639111, Tamil Nadu ' Department of Information Technology, S.A. Engineering College, Poonamallee-Avadi Road, Thiruverkadu, Chennai, 600077, Tamil Nadu, India ' Sigma University, Post Bakrol, Ajwa Road, Waghodia, Nimeta, Vadodara, Gujarat, 390019, India

Abstract: The properties of the mobile ad hoc network (MANET), such as the fast speed at which the network may be set up and the absence of the need for centralised administration, have led to the rising popularity of this network and its use in a variety of industries. One of the methods that are used to secure the network's safety is the implementation of intrusion detection systems, or IDSs. IDSs that are based on clustering have gained a lot of traction in this network owing to the benefits that they provide, such as adequate scalability. This paper presents a novel approach for use in MANETs that uses the K-nearest neighbour (KNN) algorithm for clustering. The goal of this algorithm is to identify black hole attacks. The cluster head will be determined using fuzzy inference, taking into account its history and the amount of energy that is still available.

Keywords: black hole attack; cooperative black hole attack; malicious node; packets.

DOI: 10.1504/IJMNDI.2025.146749

International Journal of Mobile Network Design and Innovation, 2025 Vol.11 No.3, pp.152 - 162

Received: 16 Nov 2024
Accepted: 30 Jan 2025
Published online: 16 Jun 2025 *

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