Practical privacy-preserving compressed sensing image recovery in the cloud

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References

  1. 1

    Baraniuk R G. Compressive sensing. IEEE Signal Process Mag, 2007, 24: 118–124

    Article  Google Scholar 

  2. 2

    Candès E J, Wakin M B. An introduction to compressive sampling. IEEE Signal Process Mag, 2008, 25: 21–30

    Article  Google Scholar 

  3. 3

    Atallah M J, Pantazopoulos K N, Rice J R, et al. Secure outsourcing of scientific computations. Adv Comput, 2002, 54: 215–272

    Article  Google Scholar 

  4. 4

    Fu Z J, Ren K, Shu J G, et al. Enabling personalized search over encrypted outsourced data with efficiency improvement. IEEE Trans Parall Distrib Syst, 2016, 27: 2546–2559

    Article  Google Scholar 

  5. 5

    Wang Q, Hu S S, Ren K, et al. Catch me in the dark: Effective privacy-preserving outsourcing of feature extractions over image data. In: Proceedings of IEEE Conference on Computer Communications (INFOCOM), San Francisco, 2016. 1–9

    Google Scholar 

  6. 6

    Wang C, Zhang B S, Ren K, et al. A privacy-aware cloud-assisted healthcare monitoring system via compressive sensing. In: Proceedings of IEEE Conference on Computer Communications (INFOCOM), Toronto, 2014. 2130–2138

    Google Scholar 

  7. 7

    Tropp J A, Gilbert A C. Signal recovery from random measurements via orthogonal matching pursuit. IEEE Trans Inf Theory, 2007, 53: 4655–4666

    MathSciNet  Article  MATH  Google Scholar 

  8. 8

    Zahur S, Rosulek M, Evans D. Two halves make a whole. In: Advances in Cryptology — EUROCRYPT 2015. Berlin: Springer, 2015. 220–250

    Google Scholar 

Download references

Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant Nos. 61379144, 61572026, 61672195), Open Foundation of State Key Laboratory of Cryptology, and Research Project of National University of Defense Technology.

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Correspondence to Shaojing Fu.

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The authors declare that they have no conflict of interest.

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Huang, K., Xu, M., Fu, S. et al. Practical privacy-preserving compressed sensing image recovery in the cloud. Sci. China Inf. Sci. 60, 098103 (2017). https://doi.org/10.1007/s11432-016-9055-2

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