DETECTION OF BLACK HOLE ATTACK USING CROSS LAYER CONCEPT IN MANET

Abstract

Mobile Nodes can communicate mutually if it falls in the sensing range of the neighboring nodes. Connected nodes can transmit, receive and forward packets to connected nodes. In this paper, we focus on detection of Black Hole attack in the MANET using the cross-layer techniques that can optimize the energy consumption. The proposed cross-layer framework contains three layers and uses parameters like mobile nodes, area and the data in network layer. The MAC and data-link layer is used as a sub-layer, and a full-duplex interface is developed through the physical (PHY) layer. Our focus here is make a secure mechanism particularly to counter Black Hole Attacks through cross-layer proposal. The proposed framework is simulated using NS-3 version NS-3.17. Our examination observes the correlation between Cross Layer and Black Hole Cross-Layer scenario. This correlation is noticed between the simulation time and mobile nodes in view of the QoS parameter like execution time, redundancy gain, average end to end delay, average throughput, and network reliability. A redundancy gain performing 100% in Cross Layer with respect to Black Hole Cross Layer, thus increases the performance of the network. The simulation results show that Cross Layer approach and detection of Black Hole in Cross Layer Network is better than Black Hole Cross Layer.