An Efficient Secure Data Aggregation Based on Homomorphic Primitives in Wireless Sensor Networks - Qiang Zhou; Geng Yang; Liwen He (International Journal of Distributed 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.