A Novel Energy-Efficient and Privacy-Preserving Data Aggregation for WSNs

Data aggregation is a fundamental and efficient algorithm to reduce the communication overhead and energy consumption in wireless sensor networks (WSNs). However, WSNs need both energy-efficient and privacy-preserving when being deployed in an unprotected area. In this paper, we propose an energy-efficient and privacy-preserving data aggregation algorithm CBDA (the chain-based data aggregation). In the CBDA, sensor nodes will be organized as a tree topology. The leaf nodes of the tree sequentially reconnect with each other to form many chain topologies. For assuring data privacy, after data gathering, <xref rid="deqn1-2" ref-type="disp-formula">(1)</xref> the tail nodes (the nodes which on the tail of chain) need to slice their sensing data into <inline-formula> <tex-math notation="LaTeX">$J$ </tex-math></inline-formula> fragments. One fragment is kept by themselves, and they distribute the <inline-formula> <tex-math notation="LaTeX">$J-1$ </tex-math></inline-formula> data fragments to their neighbor nodes. <xref rid="deqn1-2" ref-type="disp-formula">(2)</xref> Each tail node will inject some fake fragments into its <inline-formula> <tex-math notation="LaTeX">$J-1$ </tex-math></inline-formula> fragments to interfere with adversaries. The CBDA can achieve less energy consumption and higher aggregation accuracy during data aggregation. We perform a comprehensive simulation to make a comparison among the CBDA with existing algorithms. The experimental results demonstrate that the CBDA outperforms the existing algorithms.

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