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

Abstract

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.

A novel efficient approach for protecting integrity of data aggregation in wireless sensor networks

“…However, we aim to achieve preserving data privacy and integrity simultaneously in secure data aggregation in WSNs. Our proposed scheme is based on the homomorphic MAC solution, defined by Agrawal and Boneh [13], and on the two schemes SDA-HP [9] and ECIPAP [10]. However, we propose a new homomorphic MAC-based scheme, in order to provide data integrity in WSNs.…”

“…Zhou et aL. [9] propose a novel secure data aggregation scheme, named SDA-HP, based on homomorphic primitives. The scheme achieves a symmetrickey homomorphic encryption to protect privacy and combines it with homomorphic MAC to provide data integrity for aggregated data.…”

Mutual Defense Scheme for Secure Data Aggregation in Wireless Sensor Networks

“…Repeating this process, we can filter out (3) and (9) . As ( (8) − (4) ) = 11.5 − 10.1 = 1.4 < 2.0, then we finish the filtering phase and obtain the group = {10.1, 10.5, 11.0, 11.1, 11.5}.…”

Query Privacy Preserving for Data Aggregation in Wireless Sensor Networks

“…Although the schemes discussed in [26][27][28] exploited the issue of data integrity, they may cause the leakage of concealed data due to the decryption at the aggregation nodes. A proposed scheme in [29] attempted to bridge the gap between PP and data integrity through integrating an encryption algorithm with an MAC authentication mechanism, but it has the risk of putting a heavy computation burden on sensor nodes.…”