Implementing Privacy Homomorphism in Data Aggregation for Wireless Sensor Networks

Abstract

Objective: To design and implement a methodology to achieve privacy and security of data in Wireless Sensor Network (WSN) through malleability resilient concealed data aggregation protocol. Analysis: The aim of concealed collection of data in WSN is to provide privacy preservation of the data at both Intermediate Nodes (IN) and at Base Stations (BS) while aiding in-network data aggregation. The data aggregation which can be executed using privacy homomorphism at both INs and BS and is naturally malleable as the encrypted data was processed at INs without decrypting. Hence it is dreadful challenge to recognize constraints like point-to-point privacy and integrity in carrying out the aggregation. Methodology: In this paper, for protecting against passive and active adversaries in the network we propose a malleability resilient concealed data aggregation protocol. The proposed protocol protects the data from the opposing targets like privacy at both IN and at base station, point-to-point integrity, point-to-point privacy, replay protection, and aggregation. Findings/ Improvements: The major contribution of the proposed scheme verifies freshness of the data before performing encrypted data at INs as well as at BS. It also protects the data from the insider attacks as well as the outside. Thus, the protocol improves the privacy homomorphism of the data and verification of data freshness continuously at INs and also at BS.