Abstract

In Wireless Sensor Networks (WSN), the intrusion detection technique may result in increased computational cost, packet loss, performance degradation and so on. In order to overcome these issues, in this study, we propose a fuzzy based anomaly intrusion detection system for clustered WSN. Initially the cluster heads are selected based on the parameters such as link quality, residual energy and coverage. Then the anomaly intrusion is detected using fuzzy logic technique. This technique considers the parameters such as honest, energy level, unselfishness and prediction variance of each cluster member and provides the optimal trust threshold of the node as the result. By simulation result, we show that the proposed technique enhances the detection accuracy and reduces the false positive rate.

Keywords:

Anomaly IDS , cluster , fuzzy logic , metrics , WSN,

References

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.