secure data fusion in wireless multimedia sensor networks via compressed sensing

Clicks: 169
ID: 235278
2015
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Ranked #101 of 205 articles by views in BMC infectious diseases

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Abstract
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 l1-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.
Reference Key
gao2015journalsecure Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Rui Gao;Yingyou Wen;Hong Zhao
Journal BMC infectious diseases
Year 2015
DOI
10.1155/2015/636297
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