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Journal of Sensors
Volume 2015, Article ID 636297, 7 pages
Research Article

Secure Data Fusion in Wireless Multimedia Sensor Networks via Compressed Sensing

Rui Gao,1,2 Yingyou Wen,1,2 and Hong Zhao1,2

1College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
2Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang 110819, China

Received 12 September 2014; Accepted 21 March 2015

Academic Editor: Qing-An Zeng

Copyright © 2015 Rui Gao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The paper proposes a novel secure data fusion strategy based on compressed image sensing and watermarking; namely, the algorithm exploits the sparsity in the image encryption. The approach relies on -norm regularization, common in compressive sensing, to enhance the detection of sparsity over wireless multimedia sensor networks. The resulting algorithms endow sensor nodes with learning abilities and allow them to learn the sparse structure from the still image data, and also utilize the watermarking approach to achieve authentication mechanism. We provide the total transmission volume and the energy consumption performance analysis of each node, and summarize the peak signal to noise ratio values of the proposed method. We also show how to adaptively select the sampling parameter. Simulation results illustrate the advantage of the proposed strategy for secure data fusion.