Skip to main content
SpringerLink
Log in

PCS: a parity-based personal data recovery service in cloud

  • Published:
Cluster Computing Aims and scope Submit manuscript

Abstract

As more and more data are generated in an electronic format, the necessity of a data recovery service has increased, and the development of more efficient data backup and recovery technology has been an important issue during the past decade. While lots of effective backup and recovery technologies have been developed for enterprise level, little work has been done for convenient and inexpensive personal data recovery service, i.e., cloud storage service is still inadequate or expensive for backing up tera-scale HDDs. Furthermore, since privacy protection is a crucial issue for providing a personal data recovery service, a plain data backup-based recovery service is not adequate for public service. Users are reluctant to upload their data to internet backup servers until they can fully trust the service provider in terms of privacy protection. We propose a novel data recovery service framework on cloud infrastructure, a parity cloud service, which provides privacy-protected personal data recovery service while requiring a small storage space in the cloud. The proposed framework does not require any user data to be uploaded to the server, but only parity data are uploaded to the server for user data recovery. Also, the necessary server-side resources for providing the service are within a reasonable bound, depending on the data recoverability and recovery time.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Armbrust, M., et al.: Above the clouds: a Berkeley view of cloud computing. http://www.eecs.berkeley.edu/ (2009)

  2. Boru, D., Kliazovich, D., Granelli, F., Bouvry, P., Zomaya, A.Y.: Energy-efficient data replication in cloud computing datacenters. Cluster Comput. 18(1), 385–402 (2015)

    Article  Google Scholar 

  3. Casey Newton: Dropbox slashes pricing and boosts storage as competition intensifies. http://www.theverge.com/2014/8/27/6072757/dropbox-slashes-pricing-and-boosts-storage-as-competition-intensifies/ (2014)

  4. Chris Mills: Samsung’s 16TB SSD is now an actual thing people can buy. http://gizmodo.com/samsungs-16tb-ssd-is-now-an-actual-thing-people-can-buy-1762536707/ (2016)

  5. Cloud Security Alliance: Security guidance for critical areas of focus in cloud computing (2011)

  6. Dark Reading: Security is chief obstacle to cloud computing adoption, study says. http://www.darkreading.com (2009)

  7. Elerath, J.G.: A simple equation for estimating reliability of an N+1 redundant array of independent disks (RAID). In: Proceedings of IEEE/IFIP International Conference on Dependable Systems and Networks, pp. 484–493 (2009)

  8. Fitzi, M., Garay, J., Gollakota, S., Rangan, C.P., Srinathan, K.: Round-optimal and efficient verifiable secret sharing. In: Proceedings of Third Theory of Cryptography Conference, TCC ’2006 (2006)

  9. Gentry, C.: Fully homomorphic encryption using ideal lattices. In: Proceedings of the 41st ACM Symposium on Theory of Computing (STOC) (2009)

  10. Goldreich, O., Micali, S., Wigderson, A.: How to play ANY mental game. In: Proceedings of the Nineteenth Annual ACM Conference on Theory of Computing, pp. 218–219 (1987)

  11. Google: Buy, change, or cancel storage plans (of google drive). https://support.google.com/drive/answer/2375123?hl=en/ (2016)

  12. Greenan, K.M., Plank, J.S., Wylie, J.J.: Mean time to meaningless: MTTDL, Markov models, and storage system reliability. In: Proceedings of the 2nd USENIX HotStorage, Boston, MA (2010)

  13. Hao, F., Lakshman, T., Mukherjee, S., Song, H.: Secure cloud computing with a virtualized network infrastructure. In: Proceedings of the 2nd USENIX Conference on Hot Topics in Cloud Computing (2010)

  14. IETF: Extensible authentication protocol (EAP) key management framework, RFC 5247SKY. http://tools.ietf.org/html/rfc5247/ (2008)

  15. Schwarz, J.E.T., Xin, Q., Miller, E.L., Long, D.D.: Disk scrubbing in large archival storage systems. In: Proceedings of IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems (2004)

  16. Kari, H.H.: Latent sector faults and reliability of disk arrays. PhD thesis, Helsinki University of Technology (1997)

  17. Kemeny, J.G., Snell, J.L.: Finite Markov chains, 2nd edn. Springer, New York (1976)

    MATH  Google Scholar 

  18. Microsoft: Skydrive. http://skydrive.live.com/ (2015)

  19. Network World: Are security issues delaying adoption of cloud computing? http://www.networkworld.com (2009)

  20. ownCloud: ownCloud—Your Cloud, Your Data, and Your Way! http://owncloud.org/ (2015)

  21. Pearson, S.: Taking account of privacy when designing cloud computing services. In: Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing (2009)

  22. Quisquater, J.J., Guillou, L.C., Berson, T.A.: How to explain zero-knowledge protocols to your children. In: Proceedings of Advances in Cryptology—CRYPTO ’89, pp. 628–631 (1990)

  23. Schroeder, B., Gibson, G.A.: Disk failures in the real world: what does an MTTF of 1,000,000 hours mean to you? In: Proceedings of the 5th USENIX Conference on File and Storage Technologies, San Jose, CA (2007)

  24. Song, C., Park, S., Kim, D., Kang, S.: Parity cloud service: a privacy-protected personal data recovery service. In: Proceedings of the IEEE International Workshop on Trust, Security and Privacy in Internet of Things (2011)

  25. Sparkleshare: Sparkleshare—self hosted, instant, secure file sync. http://sparkleshare.org/ (2015)

  26. Wan, J., Zhang, J., Zhou, L., Wang, Y., Jiang, C., Ren, Y., Wang, J.: ORTHRUS: a lightweighted block-level cloud storage system. Cluster Comput. 16(4), 625–638 (2015)

  27. Xin, Q., Miller, E.L., Thomas Schwarz, S., Long, D.D.E.: Reliability mechanisms for very large storage systems. In: Proceedings of the 20th IEEE MSST, San Diego, CA (2003)

Download references

Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea government (No. 2014R1A2A2A01004187).

Author information

Authors and Affiliations

  1. Division of Computer Science and Engineering, Hanyang University, Seoul, South Korea

    Hyungsoo Jung, Yongsu Park, Chi-Won Song & Sooyong Kang

Authors
  1. Hyungsoo Jung
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yongsu Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chi-Won Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sooyong Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sooyong Kang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jung, H., Park, Y., Song, CW. et al. PCS: a parity-based personal data recovery service in cloud. Cluster Comput 20, 2655–2668 (2017). https://doi.org/10.1007/s10586-017-0805-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-017-0805-8

Keywords

Search

Navigation