WSNs provide promising solution in monitoring remote distributed environments. Data collected by WSNs are used for analysis and make decision. However, WSNs are vulnerable to different types of data faults due to various problems. In WSNs, transmission of data faults sent from sensor nodes to base station wasted precious energy and affected dependability of data. Such problems in WSNs can be avoided by detecting and filtering data fault using Hybrid Method (HM). In this paper we have studied the energy efficiency of two hybrid methods: HM and HM for Masking Effect. Both HM uses techniques such as Rule Based Method (RBM), Temporal Correlation Method (TCM), and Statistical Methods. Results show HM for Masking Effect is energy efficient compared to HM in the verification and validation of WSNs. Data. © 2017 Elsevier B.V., All rights reserved.