A New Data Aggregation Scheme to Support Energy Efficiency and Privacy Preservation for Wireless Sensor Networks

Because a sensor node has limited resources, such as battery capacity, data aggregation techniques have been proposed for wireless sensor networks (WSNs). On the other hand, the provision of efficient data aggregation for preserving data privacy is challenging issue in WSNs. Existing data aggregation methods for preserving data privacy are CPDA, SMART, Twin-Key based method, and GP2S. However, they have a main limitation that communication cost for network construction is considerably high. To resolve the problem, we propose a privacy preserving data aggregation scheme based on Hilbert curve for WSNs. For data aggregation, we utilize a tree-based network structure which minimizes communication among sibling sensor nodes for network construction. Moreover, we adapt a Hilbert curve technique to preserve data privacy. Because the sending data is encrypted by using a unique Hilbert value, it is very difficult to trace a real value even though attackers overhear the sending data. Through our performance analysis, we show that our data aggregation scheme outperforms the existing methods in terms of energy efficiency and privacy preservation