Volume 4, Issue 5

To Detect and Isolate the Selective Packet Drop Attack in MANET

Author

Anumati Thakur*, Max Bhatia and Bikramjit kaur

Abstract

The wireless ad hoc network is the self-configuring network; mobile nodes can leave or join the network when they want. These types of networks are much vulnerable to security attacks. Such type of active and passive attacks is possible in Ad hoc network. Among all the possible active attacks, Selective Packet Drop attack is the most common and harmful attack. The attack is triggered by the malicious node which is present in the network. In this research work, novel technique is proposed to detect and isolate malicious nodes from the network which are responsible for triggering the attack. In selective forward attack during transmission some packets gets dropped by the malicious node and that node will be acts as genuine node within the network. So incomplete data will be reach up to the destination. Therefore to detect and isolate malicious node from the network is difficult work to do. In previous work DSR Protocol was used to detect It by calculating the Energy Factor but not able to remove it completely. So, in this research work AODV protocol has been used. The new technique which is used in it is based on the Monitor Mode Approach. Through monitor mode technique messages would be flood across the channel in AODV mode and if any malicious node would be present, then instant acknowledgement would be given to source for retracing the path. This technique enhances the throughput level up to desired extent i.e. approx. 77% and other parameters like delay and packet loss also get reduced.

DOI

https://doi.org/10.62226/ijarst20150541

PAGES : 464-468 | 37 VIEWS | 87 DOWNLOADS


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Anumati Thakur*, Max Bhatia and Bikramjit kaur | To Detect and Isolate the Selective Packet Drop Attack in MANET | DOI : https://doi.org/10.62226/ijarst20150541

Journal Frequency: ISSN 2320-1126, Monthly
Paper Submission: Throughout the month
Acceptance Notification: Within 6 days
Subject Areas: Engineering, Science & Technology
Publishing Model: Open Access
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