Genetically derived secure cluster-based data aggregation in wireless sensor networks

In wireless sensor networks (WSNs), the current cluster-based data aggregation technique consumes more energy. Also the secured data transmission are vital for enhancing the data authentication and confidentiality. In order to overcome these issues, in this study, the authors propose a genetically derived secure cluster-based data aggregation in WSN. Initially the cluster heads are selected based on the node connectivity, which acts as a data aggregator. Then, the clustering process is executed using the genetic algorithm. When a cluster member wants to transmit the data to aggregator, a data encryption technique are utilised that offers authenticity, confidentiality and integrity. By simulation results, the authors show that the proposed technique minimises the energy consumption, ensures data security and reduces the transmission overhead.