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A performance analysis of black hole detection mechanisms in ad HOC networks

Publication Type : Journal Article

Thematic Areas : Wireless Network and Application

Publisher : Advances in Intelligent Systems and Computing.

Source : Advances in Intelligent Systems and Computing, Springer Verlag, Volume 398, p.433-443 (2016)

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Keywords : Ad hoc networks, AODV, Black hole attack, Cooperative mechanisms, Distributed operations, Energy utilization, Gravitation, Malignant node, MANETs, Mobile ad hoc networks, Mobile devices, Mobile security, Mobile telecommunication systems, Network Simulator2 (NS2), Packet delivery ratio, Stars, Telecommunication networks

Campus : Coimbatore

School : School of Engineering

Center : Amrita Center for Wireless Networks and Applications (AmritaWNA)

Department : Computer Science, Wireless Networks and Applications (AWNA)

Year : 2016

Abstract : A continuous infrastructure-less, self-configured collection of mobile devices connected as a network without wires is termed as mobile ad hoc network (MANET). Dynamic topology, shared physical medium, and distributed operations are some of the characteristics of MANETs due to which they are highly vulnerable to security threats. Black hole attack is a kind of attack that compromises security by redirecting the entire traffic to a node that is not actually present in the network. This paper aims to detect black hole using three detection schemes, i.e., Time-based threshold detection schemes, DRI table with cross checking scheme, and distributed cooperative mechanism. Comparative analyses on all three schemes are done to find out which one detects black hole more accurately. The measurements are taken on the light of packet delivery ratio, throughput, energy consumption and end-to-end delay. Simulation is performed using Network Simulator-2 (NS2). © Springer India 2016.

Cite this Research Publication : V. Manjusha and Dr. Radhika N., “A performance analysis of black hole detection mechanisms in ad HOC networks”, Advances in Intelligent Systems and Computing, vol. 398, pp. 433-443, 2016.

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