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