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Title:	A trust based algorithm for selfish node detection in manet using game theory
Authors:	Ahmed Adnan Hadi Al Gburi (P78913 )
Supervisor:	Zulkarnain Md. Ali, Dr.
Keywords:	Mobile network Algorithm Nodes Game theory Universiti Kebangsaan Malaysia -- Dissertations
Issue Date:	20-Mar-2017
Description:	Mobile Ad hoc network suffers from different security issues. Typically, nodes in the network might behave non-cooperating because of non-malicious intention. This is because of the node internal state such as limited energy concerns. This type of non-malicious behavior is categorized as selfish node behavior. Also, dropping packets is one security issue with a risk of harming the process of routes establishment and relaying packets. Therefore, it is very important to detect these nodes and avoid them, which guarantees improving the performance of the overall network. In this Master research work an algorithm is developed for detecting selfish node in AODV based wireless routing network based on the benchmark of (Das et al. 2015). Two algorithms were integrated for assuring least fault positive decision of selfish nodes detection; first one is to avoid false positive detection of selfish nodes in forwarding route request packet and second one is to avoid false positive detection of selfish node in forwarding data packets. For avoidance of false positive decision of selfishness in forwarding route request packet, the node sends Route Request Confirmation Packet in case a packet with the same id has been received and forwarded by the node earlier. The goal of this packet is to assure to other nodes that not sending the packet is not because of selfishness. For avoidance of false positive decision of selfish node in forwarding data packets, the sender of the data packet will update the routing table before forwarding it in order to ensure it. Results shows outperforming performance of the developed model in terms of Packet Delivery Ratio PDR with an improvement percentage of nearly 40% and in terms of E2Edelay with an improvement percentage of nearly 6%.,Certification of Master's/Doctoral Thesis" is not available
Pages:	80
Publisher:	UKM, Bangi
URI:	https://ptsldigital.ukm.my/jspui/handle/123456789/476449
Appears in Collections:	Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat

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