Wireless Sensor Networks (WSNs) are mostly vulnerable to the various attacks. The performance of the wireless sensor networks plays vital role but attacks degrades the performance. One of the attacks is the Sybil attack, in which a malicious node creates a huge number of fake identities in the network. The study indicates that the UWB ranging-based Sybil attack detection in wireless sensor network has better results but it can be improved further by utilizing the optimistic decision making technique. This research work mainly focus on the wireless sensor network which use fuzzy membership function for Sybil attack detection which further improves the WSNs. This proposed technique provides 95% accuracy and higher the value of F-measure and lower the false probability rate and error rate.

Wireless Sensor Network, Sybil attack, Fuzzy membership function

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