Title: Multi-level data fusion algorithm towards privacy protection in wireless sensor networks

Authors: Zheng Wang; Liang Li; Chen Ao; Dapeng Wu; Wenjun Zhou; Xiaojun Yu

Addresses: State Grid Key Laboratory of Power Industrial Chip Design and Analysis Technology, Beijing Smart-Chip Microelectronics Technology Co., Ltd., Beijing 100192, China ' State Grid Key Laboratory of Power Industrial Chip Design and Analysis Technology, Beijing Smart-Chip Microelectronics Technology Co., Ltd., Beijing 100192, China ' State Grid Key Laboratory of Power Industrial Chip Design and Analysis Technology, Beijing Smart-Chip Microelectronics Technology Co., Ltd., Beijing 100192, China ' Chongqing University of Posts and Telecommunications, No. 2, Chongwen Road, Nan'an District, Chongqing, China ' Wuhan University, Luojia Hill, Wuchang District, Hubei, China ' Maintenance Company of State Grid, NingXia Electric Power Co., Ltd., No. 288, Changcheng East Road, Yinchuan, Ningxia, China

Abstract: Data fusion is one of the key technologies in wireless sensor networks. To promote secure and efficient data fusion for wireless sensor networks, a privacy protection-based multi-level data fusion algorithm is proposed. In order to minimise the network energy consumption, the optimal number of cluster heads is selected and the adaptive clustering is performed according to the node energy and the positional relationship between nodes. Then, the cluster members collect and encrypt data, whereas the cluster head cleans and integrates the encrypted data. Furthermore, by analysing the correlation between data and constructing the BP neural network, cluster heads and the sink node can fuse the data in a cluster and the data between clusters to achieve the optimal data fusion. Results show that the mechanism proposed in this paper can significantly reduce resource overheads, effectively guarantee data security and fusion efficiency.

Keywords: wireless sensor network; data fusion; privacy protection; data compression; BP neural network.

DOI: 10.1504/IJCNDS.2020.109568

International Journal of Communication Networks and Distributed Systems, 2020 Vol.25 No.3, pp.265 - 283

Received: 20 Dec 2018
Accepted: 20 May 2019

Published online: 05 May 2020 *

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