Performance Comparison of Black Hole Attack Detection Mechanism in 6lowpan Over Manet

Abstract

Black Hole Attack is the most vulnerable attacks in the network layer of wireless environment. In MANET, the existing techniques were proposed to detection and mitigate the black hole attacks. Thus the environment of the MANET which is differs from the 6LoWPAN Network. The cluster based nodes are connected together to form an MANET and also these type of architecture may have used in the 6LoWPAN Network. In MANET, it should be connected with the environment of mobile nodes itself rather; in 6LoWPAN architecture the mobile nodes are connected to form a network and also the nodes in the clusters can be connect with the internet through the gateway. The severity of attacks may differ from the environment to environment. Thus the malicious nodes may vulnerable within the range of MANET. It only can be able to connect with the nodes in the MANET rather it is most vulnerable thing is to detect the black hole attack from the nodes which are connected with the internet through the gateway. In this cluster based routing protocol implementation is proposed and the performance of the black hole attack detection can be analyzed and comparatively discussed with their results based on the parameters such as positive detection rate and energy consumption for packet overhead in the attack detection.

Clustering Based Optimal Cluster Head Selection Using Bio-Inspired Neural Network in Energy Optimization of 6LowPAN

“…Every CH's datum is instantly forwarded to the BS [26]. Various surveys on energy use, energy gaps and attacks on RPL and LLP systems can be found in [27][28][29][30]. The glowworm swarm-based approach cast-off energy-based transmission strategy has been presented to decrease energy consumption caused by control overhead [31].…”