DocumentCode
3580610
Title
RTT Based Wormhole Detection Using NS-3
Author
Agrawal, Neha ; Mishra, Nitin
Author_Institution
Dept. of Inf. Technol., NRI Inst. of Sci. & Technol. Bhopal, Bhopal, India
fYear
2014
Firstpage
861
Lastpage
866
Abstract
Battery driven devices are need more routing strategy and their caring to safe against attack. WSN is also vulnerable to attack like wormhole, in which a malicious node captures packets from one location (or from intermediated path) in the network, and channelized it to the wrong direction towards another malicious node at a remote point, that recursively replays it again or start dropping. A wormhole tunnel can actually be useful if used for forwarding all the packets. However, in its malicious personification, it is used with violent nodes to suppress the correct operation of ad hoc and sensor network routing protocols. In this article a RTT estimator based wormhole detection mechanism has been proposed to identify wormhole tunneling attack in MANET. Proposed method has been evaluated and simulated using NS-3 simulator. Obtained results shows our enhance mechanisms using RTT estimator works efficiently and able to detect all the wormhole suspicious activity in wireless network. For effective simulation of wormhole, a wormhole tunnel has been create using AODV routing protocol then detection mechanism bas been enabled in conjunction with RTT estimation on the nodes.
Keywords
mobile ad hoc networks; routing protocols; telecommunication security; wireless sensor networks; AODV routing protocol; MANET; NS-3 simulator; RTT estimator based wormhole detection mechanism; WSN; ad hoc network routing protocols; battery driven devices; malicious node; remote point; routing strategy; sensor network routing protocols; wireless network; wormhole suspicious activity detection; wormhole tunneling attack identification; Mobile ad hoc networks; Routing; Routing protocols; Security; Topology; Wireless communication; AODV; DSR; MANET; NS-3; RTT; Wormhole;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Communication Networks (CICN), 2014 International Conference on
Print_ISBN
978-1-4799-6928-9
Type
conf
DOI
10.1109/CICN.2014.182
Filename
7065602
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