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Distributed compressed sensing for multi-sourced fusion and secure signal processing in private cloud

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Abstract

In this paper, a novel scheme is proposed for multi-sourced signal fusion and secure processing. Within a distributed compressed sensing (DCS) framework, traditional sampling, compression and encryption for signal acquisition are unified under the secure multiparty computation protocol. In the proposed scheme, generation of the pseudo-random sensing matrix offers a natural method for data encryption in DCS, allowing for joint recovery of multiparty data at legal users’ side. Experimental analysis and results indicate that the secure signal processing and recovery in DCS domain is feasible, and requires fewer measurements than the achievable approach of separate CS and Nyquist processing. The proposed scheme can be also extended to other cloud-based collaborative secure signal processing and data-mining applications.

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Acknowledgments

The authors would greatly thank the anonymous reviewers and the editors for their constructive comments to further improve this paper. This work was supported by the National Natural Science Foundation of China (61272381, 61571141), Science and Technology Major Project of Education Department of Guangdong Province (2014KZDXM060), and the Natural Science Foundation of Guangdong (2015A030313672), and Science and Technology Project of Guangzhou City (2014J4100078).

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Authors and Affiliations

  1. School of Electronic and Information, Guangdong Polytechnic Normal University, Guangzhou, China

    Huimin Zhao, Wenguo Wei, Jun Cai, Fangyuan Lei & Jianzhen Luo

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  1. Huimin Zhao
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  2. Wenguo Wei
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  3. Jun Cai
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  4. Fangyuan Lei
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  5. Jianzhen Luo
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Correspondence to Huimin Zhao.

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Zhao, H., Wei, W., Cai, J. et al. Distributed compressed sensing for multi-sourced fusion and secure signal processing in private cloud. Multidim Syst Sign Process 27, 891–908 (2016). https://doi.org/10.1007/s11045-015-0371-2

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  • DOI: https://doi.org/10.1007/s11045-015-0371-2

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