Predicting and diagnosing self-intermittent faults in a dynamic distributed attack on wireless sensor network
by Bhabani Sankar Gouda; Parimal Kumar Giri; Sudhakar Das; Trilochan Panigrahi; Bijay Kumar Paikaray
International Journal of Business Continuity and Risk Management (IJBCRM), Vol. 14, No. 2, 2024

Abstract: In the distributed sensor network, it is challenging to secure communication while simultaneously being aware of the intermittent failure situation of a sensor node during the connection. The existing methods rely on KNN with statistical methods and iterative to identify error-free communication for the random behaviour of the sensor node. This research developed a KNN-based method for predicting whether a transmission would be faulted or fault-free and the statistics of sensor received data over a specific time interval, time period, and amount of time measures and compares the distance statistics of the sensor node at a predetermined, specific tolerance level. Moreover, in the simulation study, the entire network is based on the sending and receiving data status in a distributed WSN for real-time measurement with 100% data accuracy, a lower FPR, and a 0% FAR. All the experimental results found the statistical distance from a problematic cluster node exceeds 30%.

Online publication date: Mon, 10-Jun-2024

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