Springer Nature is making Coronavirus research free. View research | View latest news | Sign up for updates

Practical privacy-preserving compressed sensing image recovery in the cloud

  • 81 Accesses

  • 4 Citations

This is a preview of subscription content, log in to check access.

References

  1. 1

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

  2. 2

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

  3. 3

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

  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

  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

  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

  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

  8. 8

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

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.

Author information

Correspondence to Shaojing Fu.

Additional information

The authors declare that they have no conflict of interest.

Electronic supplementary material

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

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

Download citation