Double Secure Optimal Partial Aggregation Using Trust Inference and Hybrid Syncryption Algorithm for Wireless Sensor Networks

Abstract

A reliable security mechanism for data aggregation is most wanted due to the rapid growth in wireless sensor network (WSN) applications. Many research works have been focus to obtain confidentiality and integrity. Data aggregation is a challenging process, for one of the reason security issues can arrived at aggregated node. In this paper, we propose a double secure optimal partial aggregation (DS-OPA), which provides secure data aggregation without compromise network performance. The proposed DS-OPA technique consists of two phase. In first phase, we propose multi-objective differential evolution based inference (MDEI) model to compute the trusted aggregated node among multiple nodes in neighbor. The time varying constraints gather from aggregated nodes are optimize by proposed Jaya optimization algorithm. The selected aggregation node successfully received multiple input and produce single output without loss. In second phase, we use hybrid syncryption public key algorithm used to protect data privacy, which avoid data modification in aggregated node. To demonstrate their performance, we implemented our proposed DS-OPA system in network simulator tool with large network size. The simulation results prove that our proposed DS-OPA system are perfectly suited than existing systems.