Detecting and Denying Malicious Behavior using Adaptive Learning based Routing Protocol in Wireless Mesh Network

Authors

R. Regan, Department of CSE, University College of Engineering, Villupuram, Anna University, IndiaFollow
J. Martin Leo Manickam, Department of ECE, St.Joseph’s College of Engineering, Chennai, IndiaFollow

Author Country (or Countries)

India

Abstract

Wireless Mesh Network (WMN) is a self organization and self configuration network which provides fast internets based on hybrid network. WMN consists of mesh nodes and mesh routers which provide security to sufficiently analyze the location but its performance is degraded when it comes to its overhead. WMN provides different security solutions at different levels of its layers. Each and every layer encounters attacks by the malicious behavior program which is due to the presence of its layers. So, in this paper, we propose a new framework solution against wormhole attacks based on adaptive learning technique, which provides mesh node level security and cluster head level security for avoiding wormhole attack. This framework focuses on routing layer which updates malicious node details and faster analysis of mesh routers. The performance has improved in terms of packet delivery ratio, routing overhead, throughput, and end to end delay compared to the Control Traffic tunneling Attacks Countermeasure (CTAC)

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/amis/110423

Recommended Citation

Regan, R. and Martin Leo Manickam, J. (2017) "Detecting and Denying Malicious Behavior using Adaptive Learning based Routing Protocol in Wireless Mesh Network," Applied Mathematics & Information Sciences: Vol. 11: Iss. 4, Article 23.
DOI: http://dx.doi.org/10.18576/amis/110423
Available at: https://digitalcommons.aaru.edu.jo/amis/vol11/iss4/23