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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 1/2020

22.04.2020

Neuro-Fuzzy Based Intrusion Detection System for Wireless Sensor Network

verfasst von: Somnath Sinha, Aditi Paul

Erschienen in: Wireless Personal Communications | Ausgabe 1/2020

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Abstract

Malicious attacks like denial-of-service massively affect the network activities of wireless sensor network. These attacks exploit network layer vulnerabilities and affect all the layers of the network. Anomaly based intrusion detection system (AIDS) are designed for monitoring such unpredictable attacks but it generates high false positive. In the proposed study we design robust and efficient AIDS which use fuzzy and neural network (NN) based tools. The proposed system can be implemented in each node as it is lightweight and does not consume much overhead. Also it can independently monitor the local nodes behaviour and identify whether a node is trust, distrust or enemy. The use of a trained NN filters the false alarms generated due to fuzzy logic applied in the first step thus enhancing the system accuracy. We evaluate the system’s performance in NS2.35 and result shows a 100% true positive with 0% false positive.
Vorheriger Artikel An Integrated Trust Assisted Energy Efficient Greedy Data Aggregation for Wireless Sensor Networks
Nächster Artikel Ring Signature-Based Conditional Privacy-Preserving Authentication in VANETs

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Metadaten
Titel
Neuro-Fuzzy Based Intrusion Detection System for Wireless Sensor Network
verfasst von
Somnath Sinha
Aditi Paul
Publikationsdatum
22.04.2020
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 1/2020
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-020-07395-y

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