A hierarchical secure data aggregation method using the dragonfly algorithm in wireless sensor networks

Abstract

A wireless sensor network (WSN) consists of a set of sensor nodes that are widely scattered in inaccessible areas. When deployed in large areas, WSNs generate a large volume of the data. Therefore, efficient methods are needed to process the data. One solution to minimize traffic on large-scale wireless sensor networks is to use data aggregation schemes. In this paper, a secure data aggregation method is proposed. The proposed secure data aggregation scheme has three phases: intra-cluster data aggregation, inter-cluster data aggregation, and data transfer. In the intra-cluster data aggregation phase, a fuzzy scheduling system is designed to adjust the appropriate data transmission rates of the cluster member nodes. In the inter-cluster data aggregation phase, an aggregation tree is created between the cluster head nodes. The dragonfly algorithm (DA) is used to find the optimal aggregation tree between cluster head nodes. In the data transfer phase, the columnar transposition cipher method is used to establish a secure connection between cluster member nodes and their cluster head node. Also, a symmetric and lightweight encryption method based on the residue number system (RNS) is utilized to provide secure communications between the cluster head nodes. We modify RNS and call it RNS+. Finally, the simulation results of the proposed scheme are compared to three data aggregation methods including Sign-share, Sham-share, and RCDA. The results show that the proposed data aggregation scheme outperforms other data aggregation methods in terms of network lifetime, delay and packet delivery rate.