An approach to detect black hole attack for congestion control utilizing mobile nodes in wireless sensor network

Abstract

Mobile ad-hoc Network (MANET) is temporary and dynamic network topology, wherein nodes are mobile in nature with bandwidth and resource constraint. Applications of MANET’s are widely used in different areas. Provisioning of quality of service (QoS) for routing in MANET’s is a challenging issue. Packet drop occurs due to congestion related issues like limited bandwidth, link failure and interference also misbehaving node drops the packet to harm the network. Differentiating packet loss due to congestion or malicious node is a tedious job. Securing the mobile nodes from attacker has become one of the crucial aspects of providing QoS, since nodes are weak to different kinds of attacks and threats that impact network connectivity and functionality. The black-hole attack is examined to be epidemic and popular active attack that degrades overall reliability and network performance by dropping all the incoming packets. In Black-hole node pretends that it has a shortest route to destination and intent to deceive every node in the network. In this paper we differentiate packet loss due to congestion or by malicious node, our scheme utilises on-demand link and energy aware dynamic multipath (O-LEADM) routing scheme for MANET’s to detect black-hole node by integrating bait method, the behaviour of node is analysed using control messages destination-sequence (des-Seq) and reply-sequence (rep-Seq) while accessing the channel. During route discovery each intermediated node in the network sends the des-Seq message to all its neighbour nodes, and then neighbour nodes intern replies to intermediate node by sending rep-Seq message. If des-Seq and req-Seq from the neighbours does not match, then node is said to be malicious. Connection to the network layer is allowed to intermediate node if des-Seq and rep-Seq matches. Channel availability and link quality parameter estimates the link stability thus nodes select forwarding based on their behaviour and capable of achieving QoS parameters such as link quality, residual energy and higher packet delivery. Simulation under various network conditions is experimented using Network simulator tool (NS2) and using parameters the performance metric is in terms of delay, packet delivery ratio, overhead and energy are evaluated.