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Neighbor Constraint Traffic Centric Distributed Sinkhole Detection and Mitigation Approach for Quality of Service Improvement in Wireless Sensor Networks

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Industry Interactive Innovations in Science, Engineering and Technology

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 11))

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Abstract

In Wireless Sensor Networks (WSN), the problems of sinkhole detection and mitigation have been studied through various methods, but suffer with the problems of high complex detection and overhead introduced by detection process. The Quality of Service (QoS) has been degraded greatly by the impact of sinkhole attack because the malicious node can read much information about the source or the communications; this helps malicious nodes to perform various kinds of attacks. In order to overcome such drawbacks of network security, in this paper propose a Neighbor Constraint Traffic Centric (NCTC) Method for sinkhole detection to support QoS development of WSN. The problem of multiple identifications is resolved by verifying the transmission performed through other neighbors of the malicious node. From the traffic incurred in the neighbor of malicious node is used to verify the location or traffic sent by the malicious node. The method produces efficient results in sinkhole detection and increases the throughput and also the packet delivery ratio and reduces the frequency of sinkhole detection.

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Correspondence to K. Devibala .

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Devibala, K., Balamurali, S., Ayyasamy, A., Archana, M. (2018). Neighbor Constraint Traffic Centric Distributed Sinkhole Detection and Mitigation Approach for Quality of Service Improvement in Wireless Sensor Networks. In: Bhattacharyya, S., Sen, S., Dutta, M., Biswas, P., Chattopadhyay, H. (eds) Industry Interactive Innovations in Science, Engineering and Technology . Lecture Notes in Networks and Systems, vol 11. Springer, Singapore. https://doi.org/10.1007/978-981-10-3953-9_34

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  • DOI: https://doi.org/10.1007/978-981-10-3953-9_34

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  • Print ISBN: 978-981-10-3952-2

  • Online ISBN: 978-981-10-3953-9

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