Skip to main content

Optimal Storage Cloud Data Recoverability Audit Method Based on Regenerative Code

  • Conference paper
  • First Online:
Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1491))

  • 827 Accesses

Abstract

In cloud data security storage, when data holders store 1ocally controllable data resources in the cloud, they lose control of data integrity and availability. For data holders, the cloud service provider CSP is untrustworthy, and it may damage the data stored in the cloud or forge and deceive the integrity of the damaged data. Aiming at the data recoverability problem after detecting data integrity damage in cloud data storage, an audit method of optimal storage cloud data recoverability based on regeneration code is proposed. This solution not only supports the third-party audit agency to verify whether the data block is damaged and locate the exact location of the damaged data block, but also realizes the data integrity recovery function. In the process of data processing and auditing, the privacy and safety of data are guaranteed. Experiments have proved that the program has a certain degree of safety and effectiveness.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Mell, P.M., Grance, T.: SP 800-145. The NIST Definition of Cloud Computing. National Institute of Standards and Technology vol. 53, issue 6, pp. 50–50 (2011)

    Google Scholar 

  2. Xuelong, L., Haigang, G.: Overview of big data system. Sci. China Inf. Sci. 45(1), 1–44 (2015)

    Google Scholar 

  3. Chaosheng, F., Zhiguang, Q., Ding, Y.: Cloud data security storage technology. Chin. J. Comput. 38(001), 150–163 (2015)

    Google Scholar 

  4. Dengguo, F., Min, Z., Hao, L.: Big data security and privacy protection. Chin. J. Comput. 01, 246–258 (2014)

    Google Scholar 

  5. Dimakis, A.G., Godfrey, P.B., Wu, Y., et al.: Network coding for distributed storage systems. IEEE Trans. Inf. Theory 56(9), 4539–4551 (2010)

    Article  Google Scholar 

  6. Chen, L.: Using algebraic signatures to check data possession in cloud storage. Future Gener. Comput. Syst. FGCS 29(7) (2013)

    Google Scholar 

  7. Rashmi, K.V., Shah, N.B., Kumar, P.V.: Optimal exact-regenerating codes for distributed storage at the MSR and MBR points via a product-matrix construction. IEEE Trans. Inf. Theory 57(8), 5227–5239 (2011)

    Article  MathSciNet  Google Scholar 

  8. Miao, B., Song, M., et al.: A transformation principle of regenerated code for heterogeneous distributed storage. Mod. Electron. Techn. 42(24), 104–107(2019)

    Google Scholar 

  9. Diffie, W., Hellman, M.: New directions in cryptography. IEEE Trans. Inf. Theory 22(6) (1976)

    Google Scholar 

  10. Shah, N.B., Rashmi, K.V., Kumar, P.V.: A flexible class of generating codes for distributed storage. In: Proceeding of IEEE International Symposium on Information Theory (1SIT), pp. 1943–1947. Austin, Juru (2010)

    Google Scholar 

  11. Qing, Z., Wang, S., et al.: An auditing protocol for data storage in cloud computing with data dynamics. J. Comput. Res. Develop. 52(10), 2192–2199 (2015)

    Google Scholar 

  12. Jing, C., Peng, Y., Du, R., et al.: Regenerating-codes-based efficient remote data checking and repairing in cloud storage. In: 2015 IEEE Trustcom/BigDataSE/ISPA, pp. 20–22. IEEE (2015)

    Google Scholar 

  13. Liu, J., Huang, K., Rong, H., et al.: Privacy-preserving public auditing for regenerating-code-based cloud storage. IEEE Trans. Inf. Forensics Secur. 10(7), 1 (2015)

    Article  Google Scholar 

  14. Kai, H., Huang, C., Shi, J., et al.: Public integrity auditing for dynamic regenerating code based cloud storage. Computers & Communication. IEEE (2016)

    Google Scholar 

  15. Liu, C., Chen, J., Yang, L.T., et al.: Authorized public auditing of dynamic big data storage on cloud with efficient verifiable fine-grained updates. IEEE Trans. Parallel Distrib. Syst. 25(9), 2234–2244 (2014)

    Article  Google Scholar 

  16. Liu, C., Ranjan, R., Yang, C., et al.: MuR-DPA: top-down levelled multi-replica merkle hash tree based secure public auditing for dynamic big data storage on cloud. IEEE Trans. Comput. 64(9), 2609–2622 (2015)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yinzhang Guo .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Li, X., Guo, Y., Han, T. (2022). Optimal Storage Cloud Data Recoverability Audit Method Based on Regenerative Code. In: Sun, Y., et al. Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2021. Communications in Computer and Information Science, vol 1491. Springer, Singapore. https://doi.org/10.1007/978-981-19-4546-5_9

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-4546-5_9

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-4545-8

  • Online ISBN: 978-981-19-4546-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics