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Detecting Blackhole Attack using Encounter Records on Multi-Copy Routing Protocols in Delay Tolerant Networks (DTN)
Author(s) -
Heru Nurwarsito,
Naldo Sirait
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.c1034.0193s20
Subject(s) - computer network , computer science , network packet , relay , packet drop attack , overhead (engineering) , node (physics) , routing protocol , routing (electronic design automation) , blacklist , link state routing protocol , engineering , power (physics) , physics , structural engineering , quantum mechanics , operating system
Delay Tolerant Network (DTN) is a solution for intermittent connectivity and high delay. However, due to constrained connectivity, DTN is vulnerably susceptible to Blackhole attacks in which malicious nodes will drop all packets received from source nodes or relay nodes. The impact of a Blackhole attack can reduce the packet delivery ratio and waste resources from relay nodes that carry and forward messages. The encounter record scheme is one solution that can be applied to detect Blackhole attacks on the DTN. The encounter record mechanism is performed by utilizing a relay node that will store several records obtained from encounters between previous nodes, then the node will detect when a packet has dropped and a blacklist is performed on the node detected as a malicious node. Based on testing the performance of the routing protocol obtained that the encounter record scheme is able to detect malicious nodes so that it can again increase the delivery ratio and overhead ratio. The simulation results of this research showed that the Encounter Record has successfully detected Blackhole attacks with an average detection time of 1,5992 seconds in the spray-and-wait routing and 1,5342 seconds in the epidemic routing for 15 malicious nodes. Detection accuracy is 100% on spray-and-wait routing and 73,85% on routing epidemic for 15 malicious nodes.

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