A Secured and Guaranteed Packet Transmission across Multiple Nodes in Mobile Adhoc Networks with Presence of Malicious Monitoring Nodes

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-40 Number-1
Year of Publication : 2016
Authors : S.Sathish kumar, P.Vijayakumar
  10.14445/22312803/IJCTT-V40P102

MLA

S.Sathish kumar, P.Vijayakumar "A Secured and Guaranteed Packet Transmission across Multiple Nodes in Mobile Adhoc Networks with Presence of Malicious Monitoring Nodes". International Journal of Computer Trends and Technology (IJCTT) V40(1):5-9, October 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
MANET consists of self organized mobile nodes. For effective maintenance of network, these mobile nodes should collaborate together. But, some nodes in the network may fail to cooperate and show selfish behavior. The presence of selfish nodes in the network reduces the performance of packet transmission. Watchdog systems are used in the detection of selfish nodes. Hence, collaborative contact-based watchdog (CoCoWa) approach was proposed by which selfish nodes, new contacts and malicious nodes were detected by using local watchdogs. This approach enhanced the effectiveness of detecting selfish nodes. In our proposed system, malicious nodes are detected by periodically monitoring the behavioural changes of each node. The observed changes are used to construct the behaviour matrix. Kullback-Leibler divergence (KL divergence) is then used to calculate the divergence rate of nodes from behaviour matrix and identifies the malicious nodes. But, when the argument values used in KL divergence are reversed, then it show different results because is a non-symmetric divergence. This results leads to the accuracy problem. Hence, our proposed work uses different forms of mixture of directed and alternate Kullback–Leibler divergences for symmetrizing the Kullback–Leibler Divergence. Based on the obtained symmetric measures, Akaike information criterion (AIC) is then used for improving accuracy results by selecting the malicious nodes effectively.

References
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Keywords
Watchdog system, malicious nodes, Kullback-Leibler divergence and Akaike information criterion.