An Efficient Secure Data Aggregation Based on Homomorphic Primitives in Wireless Sensor Networks

Data aggregation is an important method to reduce the energy consumption in wireless sensor networks (WSNs); however, it suffers from the security problems of data privacy and integrity. Existing solutions either have large communication and computation overheads or only produce inaccurate results. This paper proposes a novel secure data aggregation scheme based on homomorphic primitives in WSNs (abbreviated as SDA-HP). The scheme adopts a symmetric-key homomorphic encryption to protect data privacy and combines it with homomorphic MAC synchronically to check the aggregation data integrity. It compares the scheme with the previously known methods such as SIES, iPDA, and iCPDA in terms of the data privacy protection efficiency, integrity performance, computation overhead, communication overhead, and data aggregation accuracy. Simulation results and performance analysis show that our SDA-HP requires less communication and computation overheads than previously known methods and can effectively preserve data privacy, check data integrity, and achieve high data transmission efficiency and accurate data aggregation rate while consuming less energy to prolong network lifetime. To the best of our knowledge, this is the first work that provides both integrity and privacy based on homomorphic primitives. 1. Introduction Currently, wireless sensor networks (WSNs) have many popular applications, such as real-time accident reporting, environment monitoring, and military investigation. In WSNs, sensors are deployed to gather different kinds of data within a certain range and send them to the base station (BS). Sensors are restricted by energy consumption due to battery supply and computational capacity; therefore, energy saving technologies must be considered. Data aggregation [1] is one of the important approaches to facilitate the utilization of WSNs. However, WSNs are often deployed in an open and hostile environment; the inherent characteristics of WSNs and data aggregation algorithms make WSNs data aggregation face many security and performance challenges, such as data integrity; privacy protection, and how to enhance the security and performance becomes the key issues for practical applications. In recent years, some schemes [2–5] have been proposed focusing on guaranteeing the data privacy during data aggregation phase, but these do not protect the integrity of aggregation data sent to the BS. A compromised aggregator may arbitrarily forge aggregation data and let the BS accept them. Other schemes [6–8] are proposed to guarantee the data integrity, but these