Fuzzy Trust Evaluation and Secure K-Means Clustering with Trust-Based Outlier Detection (SKC-TOD) in Wireless Sensor Networks (WSNs)

Abstract

Secure communication and Secure Data Transmission (SDT) were considered as one of the major challenges in the Wireless Sensor Networks (WSN). Here, Fuzzy Trust Evaluation and Secure K-Means Clustering (KMC) with the Trust-based Outlier Detection (OD) Secure K-means Clustering Trust-based Outlier Detection (SKC-TOD) method was suggested in this study. The  Data Transmission (DT) and evidence in Trust Values (TV) supports the Fuzzy Trust Evaluation for improving the trust of connections among the Sensor Nodes (SN). The Fuzzy C-Means (FCM) approach is used to arrange the SN into uniformly distributed clusters. This FCM method also contributes in determining the optimal Cluster Head (CH) Cluster Head Selection (CHS). The suggested SKC-TOD method was employed for enhancing accuracy. The processing time was also reduced by this suggested method. Finally, the SDT was also ensured by this suggested method. When comparing the suggested method to other current methods, the suggested method performs better than the current methods. Here, ensuring the SDT becomes a complex task for conventional methods. Then, TOD system helps in strengthening the Data Integrity (DI) against both internal and external risks. The Malicious Nodes (MN) were effectively detected and gets isolated by this TOD system. The comparative analysis was conducted among the suggested SKC-TOD and current Fuzzy clustering protocols. Form the analysis, it is clear that the suggested method is effective in enhancing SDT than the current fuzzy clustering protocols. For ensuring SDT in WSN, this suggested SKC-TOD is an effective method.