Wireless Sensor Networks (WSNs) consist of numerous small, multifunctional sensor nodes deployed in target areas to collect and transmit environmental data. Due to the energy constraints of battery-powered nodes, balancing energy consumption with network performance remains a significant challenge. To address this, an approach integrating Artificial Neural Network (ANN)-based outlier detection with a secure and energy-efficient data transmission mechanism using an enhanced LEACH protocol is proposed. Nodes are initialized in the sensing region to gather informations. Then Artificial Neural Network is utilized to identify the outliers from the deployed nodes. Then, cluster formation and cluster head selection are done by employing a stable and secure LEACH protocol. A hybrid reputation-based secure data transmission (HRSDT) is employed to transfer data from its base station after CH selection. Community and QoS reputation rates are employed for sensor node reputation calculation. Among all nodes, the node with the highest HRSDT is regarded as the forward node for safe data transfer. According to the assessment results, the proposed approach obtains 92% PDR and 1.82 Mbps throughput. Therefore, the proposed technique is the optimum option for WSN data transfer as it is simultaneously secured and energy-efficient.
Tabbassum et al. (Sun,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: