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Event-driven Wireless Sensor Networks (WSNs) consist of thousands of tiny nodes. Sensor nodes are prone to faults because of their fragility and the fact that they are typically placed in harsh environments. Erroneous readings pose a high risk in many situations and affect the network&#x2019;s reliability, necessitating a solution to distinguish between true and faulty events. In response to this challenge, this work proposes the Friendship Degree and Tenth Man Strategy (FD-TMS) method for true event detection in WSNs. This new method can differentiate between erroneous readings and true events in a distributed manner. The FD idea has previously been used to solve security problems, while military intelligence operations have inspired the TMS and have never been used in WSNs. The FD-TMS consists of two stages. In the first stage, it employs a majority voting approach considering the friendship degree among voters. Voting among only trustworthiness nodes with high FD values will effectively differentiate true events and incorrect measurements. The second stage will validate the voting process through a novel perspective based on the TMS. TMS will check the voters&#x2019; replies based on the event&#x2019;s location. The proposed method will delete erroneous readings, while only the true event reports will be reported. FD-TMS was comprehensively assessed in a simulation environment utilizing a performance analysis tool constructed on Java. The results were compared to the baseline algorithm, highlighting key parameters like false alarms and event detection accuracy. The simulation results demonstrated the proposed approach significantly enhanced the performance of the baseline works.

Friendship Degree and Tenth Man Strategy: A New Method for Differentiating between Erroneous Readings and True Events in Wireless Sensor Networks