Secure Data Fusion in Wireless Multimedia Sensor Networks via Compressed Sensing
Joint Authors
Gao, Rui
Wen, Yingyou
Zhao, Hong
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-06-07
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Gao, Rui& Wen, Yingyou& Zhao, Hong. 2015. Secure Data Fusion in Wireless Multimedia Sensor Networks via Compressed Sensing. Journal of Sensors،Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1070165
Modern Language Association (MLA)
Gao, Rui…[et al.]. Secure Data Fusion in Wireless Multimedia Sensor Networks via Compressed Sensing. Journal of Sensors No. 2015 (2015), pp.1-7.
https://search.emarefa.net/detail/BIM-1070165
American Medical Association (AMA)
Gao, Rui& Wen, Yingyou& Zhao, Hong. Secure Data Fusion in Wireless Multimedia Sensor Networks via Compressed Sensing. Journal of Sensors. 2015. Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1070165
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1070165