Title: Cluster-based multiple malicious node detection using honeypot-AODV in MANETs

Authors: H.K. Sampada; K.R. Shobha

Addresses: Department of Electronics and Communication Engineering, Atria IT, Bangalore, India ' Department of Telecommunication Engineering, MSRIT, Bangalore, India

Abstract: Security and scalability are two major research areas in the field of mobile ad-hoc networks (MANETs). The existing solutions for security and scalability are majorly used for static networks, e.g., sensor networks. The focus of the present work is to detect and remove the multiple malicious black holes (MBH) and multiple malicious grey hole (MGH) nodes from the dynamic networks, e.g., MANETs. The proposed solution increases network security. An efficient weight-based clustering technique is used to enhance the stability and load balancing of the network. Cluster head (CH) is selected based on the maximum weight factor. The weight of the node is based on three factors: constancy factor (C_x) trust value (T_y) and link factor (L_z). Weightage values for the parameters can be prioritised and tested for consistency using analytic hierarchy process (AHP) algorithm. Each CH executes honeypot-AODV (H-AODV) to find the MBH and MGH nodes in its network.

Keywords: mobile ad hoc networks; MANETs; honeypot-AODV; H-AODV; modified-AODV; M-AODV; clustering; malicious blackhole/grayhole attack; MBH/MGH.

DOI: 10.1504/IJCNDS.2024.135080

International Journal of Communication Networks and Distributed Systems, 2024 Vol.30 No.1, pp.1 - 29

Received: 08 Jun 2022
Accepted: 17 Nov 2022
Published online: 30 Nov 2023 *

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