2017 11th International Conference on Intelligent Systems and Control (ISCO) 2017
DOI: 10.1109/isco.2017.7856012
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CRCMD&R: Cluster and Reputation based cooperative malicious node Detection & Removal scheme in MANETs

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Cited by 10 publications
(7 citation statements)
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“…This trust value is compared with threshold value to declare it as genuine or malicious. CRCMD&R 93 cluster head to store the information about the nodes in each cluster. Authors proposed two different algorithms to detect and remove the malicious nodes from the network.…”
Section: Cluster-based Schemesmentioning
confidence: 99%
“…This trust value is compared with threshold value to declare it as genuine or malicious. CRCMD&R 93 cluster head to store the information about the nodes in each cluster. Authors proposed two different algorithms to detect and remove the malicious nodes from the network.…”
Section: Cluster-based Schemesmentioning
confidence: 99%
“…Revoked nodes with little reliability can acts as malicious nodes. Certification authority is for monitoring the nodes behavior and is used for updating warned list and black list of malicious nodes [4].…”
Section: Related Workmentioning
confidence: 99%
“…The recommendation method showed the results for improving throughput and packet loss against untrusty nodes comparing with existing methods. Saurabh Sharma & Sapna Gambhir [4] proposed the method for detecting and removal of malicious nodes by using cluster and reputation based schemes in mobile ad-hoc networks. This scheme cluster head should maintain three tables namely legitimacy table, reputation table and neighbor table for keeping all the node information which is done by AODV reactive routing protocol.…”
Section: Related Workmentioning
confidence: 99%
“…Other types of attacks are routing attacks namely Black hole attack, Grey Hole attack, Sleep Deprivation attack, Flooding attack, Rushing attack, Sybil attack, Worm Hole attack. There are many methods proposed for detecting malicious attacks namely watchdog and path rater, TWOACK, AACK, EAACK intrusion detection based approaches [1][2][3][4][5][6].…”
Section: Introductionmentioning
confidence: 99%