Skip to main content
SpringerLink
Log in

New Publicly Verifiable Cloud Data Deletion Scheme with Efficient Tracking

  • Conference paper
  • First Online:
Book cover Security with Intelligent Computing and Big-data Services (SICBS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 895))

Abstract

Cloud storage service, one of the most important services in the cloud computing, can offer high-quality storage service for tenants. By employing the cloud storage service, the resource-constraint data owners can outsource their data to the remote cloud server to reduce the heavy storage burden. Due to the attractive advantages, there are an increasing number of data owners prefer to embrace the cloud storage service. However, the data owners will lose the direct control over their outsourced data, and they can not directly execute operations over their outsourced data, such as data deletion operation. That will make outsourced data deletion become a crucial security problem: the selfish cloud server may not honestly perform the data deletion operation for economic interests, and then returns error results to mislead the data owners. Although a series of solutions have been proposed to solve this problem, most of them can be described as “one-bit-return” protocol: the storage server removes the data and then returns a one-bit deletion reply, and the data owners have to trust the deletion reply because they can not verify it conveniently.

In this paper, we put forward a new publicly verifiable data deletion scheme with efficient tracking for cloud storage. In our novel scheme, the remote cloud server executes the data deletion operation and returns a deletion proof. If the remote cloud server maliciously reserves the data backups, the data owner can easily detect the malicious data reservation by verifying the returned deletion proof. Besides, we utilize the primitive of Merkle Hash Tree to solve the problem of public verifiability in data deletion. Furthermore, our scheme can realize efficient data leakage source tracking when the data are leaked, which can prevent the data owner and the cloud server from exposing the data designedly to slander each other. Finally, we prove that our novel scheme can satisfy the desired security properties.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bauer, S., Priyantha, N.B.: Secure data deletion for Linux file systems. In: Proceedings of the 10th Conference on USENIX Security Symposium, vol. 174, pp. 153–164. USENIX Association, Berkeley (2001)

    Google Scholar 

  2. Boneh, D., Lipton, R.: A revocable backup system. In: Proceedings of the 6th Conference on USENIX Security Symposium, vol. 6, pp. 91–96. USENIX Association, Berkeley (1996)

    Google Scholar 

  3. Chen, X., Li, J., Ma, J., Tang, Q., Lou, W.: New algorithms for secure outsourcing of modular exponentiations. IEEE Trans. Parallel Distrib. Syst. 25(9), 2386–2396 (2014)

    Article  Google Scholar 

  4. Chen, X., Li, J., Huang, X., Li, J., Xiang, Y., Wong, D.: Secure outsourced attribute-based signatures. IEEE Trans. Parallel Distrib. Syst. 25(12), 3285–3294 (2014)

    Article  Google Scholar 

  5. Chen, X., Huang, X., Li, J., Ma, J., Lou, W., Wong, D.: New algorithms for secure outsourcing of large-scale systems of linear equations. IEEE Trans. Inf. Forensics Secur. 10(1), 69–78 (2015)

    Article  Google Scholar 

  6. Chen, X.F., Li, J., Weng, J., Ma, J., Lou, W.: Verifiable computation over large database with incremental updates. IEEE Trans. Comput. 65(10), 3184–3195 (2016)

    Article  MathSciNet  Google Scholar 

  7. Chen, X., Li, J., Huang, X., Ma, J., Lou, W.: New publicly verifiable databases with efficient updates. IEEE Trans. Dependable Secur. Comput. 12(5), 546–556 (2015)

    Article  Google Scholar 

  8. Diesburg, S., Wang, A.: A survey of confidential data storage and deletion methods. ACM Comput. Surv. 43(1), 1–37 (2010)

    Article  Google Scholar 

  9. Garfinkel, S., Shelat, A.: Remembrance of data passed: a study of disk sanitization practices. IEEE Secur. Priv. 99(1), 17–27 (2003)

    Article  Google Scholar 

  10. Gutmann, P.: Secure deletion of data from magnetic and solid-state memory. In: Proceedings of the Sixth USENIX Security Symposium, vol. 14, pp. 77–89. USENIX Association, Berkeley (1996)

    Google Scholar 

  11. Hao, F., Clarke, D., Zorzo, A.: Deleting secret data with public verifiability. IEEE Trans. Dependable Secur. Comput. 13(6), 617–629 (2016)

    Article  Google Scholar 

  12. Hughes, G., Coughlin, T., Commins, D.: Disposal of disk and tape data by secure sanitization. IEEE Secur. Priv. 7(4), 17–27 (2009)

    Article  Google Scholar 

  13. Li, J., Zhang, Y., Chen, X., Xiang, Y.: Secure attribute-based data sharing for resource-limited users in cloud computing. Comput. Secur. 72, 1–12 (2018)

    Article  Google Scholar 

  14. Li, Y., Gai, K., Qiu, L., Qiu, M., Zhao, H.: Intelligent cryptography approach for secure distributed big data storage in cloud computing. Inf. Sci. 387, 103–115 (2017)

    Article  Google Scholar 

  15. Luo, Y., Xu, M., Fu, S., Wang, D.: Enabling assured deletion in the cloud storage by overwriting. In: Proceedings of the 4th ACM International Workshop on Security in Cloud Computing, pp. 17–23. ACM, New York (2016)

    Google Scholar 

  16. Lee, J., Yi, S., Heo, J., Park, H., Shin, S.Y., Cho, Y.: An efficient secure deletion scheme for flash file systems. J. Inf. Sci. Eng. 26(1), 27–38 (2010)

    Google Scholar 

  17. Merkle, R.C.: Protocols for public key cryptosystems. In: Proceedings of the 1980 IEEE Symposium on Security and Privacy (SP), pp. 122–134. IEEE Computer Society, Washington, DC (1980)

    Google Scholar 

  18. Miao, M., Wang, J., Ma, J., Susilo, W.: Publicly verifiable databases with efficient insertion/deletion operations. J. Comput. Syst. Sci. 86, 49–58 (2017)

    Article  MathSciNet  Google Scholar 

  19. Ni, J., Lin, X., Zhang, K., Yu, Y., Shen, X.: Secure outsourced data transfer with integrity verification in cloud storage. In: Proceedings of the 2016 IEEE/CIC International Conference on Communications in China, ICCC 2016, pp. 1–6. IEEE Computer Society, Washington, DC (2016)

    Google Scholar 

  20. Paul, M., Saxena, A.: Proof of erasability for ensuring comprehensive data deletion in cloud computing. In: Meghanathan, N., Boumerdassi, S., Chaki, N., Nagamalai, D. (eds.) Recent Trends in Network Security and Applications, CNSA 2010. CCIS, vol. 89, pp. 340–348. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  21. Perito, D., Tsudik, G.: Secure code update for embedded devices via proofs of secure erasure. In: Gritzalis, D., Preneel, B., Theoharidou, M. (eds.) Computer Security C ESORICS 2010, ESORICS 2010. LNCS, vol. 6345, pp. 643–662. Springer, Heidelberg (2010)

    Google Scholar 

  22. Perlman, R.: File system design with assured delete. In: Proceedings of the Third IEEE International Security in Storage Workshop (SISW 2005), pp. 83–88. IEEE Computer Society, Washington, DC (2005)

    Google Scholar 

  23. Rahumed, A., Chen, H.C., Tang, Y., Lee, P.P., Lui, J.C.: A secure cloud backup system with assured deletion and version control. In: Proceedings of the 2011 40th International Conference on Parallel Processing Workshops (ICPPW), pp. 160–167. IEEE Computer Society, Washington, DC (2011)

    Google Scholar 

  24. Reardon, J., Basin, D., Capkun, S.: SoK: secure data deletion. In: Proceedings of the 2013 IEEE Symposium on Security and Privacy (SP), pp. 301–315. IEEE Computer Society, Washington, DC (2013)

    Google Scholar 

  25. Stergiou, C., Psannis, K.E., Kim, B.G., Gupta, B.: Secure integration of IoT and cloud computing. Future Gener. Comput. Syst. 78, 964–975 (2018)

    Article  Google Scholar 

  26. Tang, Y., Lee, P., Lui, J., Perlman, R.: Secure overlay cloud storage with access control and assured deletion. IEEE Trans. Dependable Secur. Comput. 9(6), 903–916 (2012)

    Article  Google Scholar 

  27. Tian, H., Chen, Y., Chang, C., Jiang, H., Huang, Y., Chen, Y., Liu, J.: Dynamic-hash-table based public auditing for secure cloud storage. IEEE Trans. Serv. Comput. 10(5), 701–714 (2017)

    Article  Google Scholar 

  28. Wang, J., Chen, X., Huang, X., You, I., Xiang, Y.: Verifiable auditing for outsourced database in cloud computing. IEEE Trans. Comput. 64(11), 3293–3303 (2015)

    Article  MathSciNet  Google Scholar 

  29. Wang, Y., Tao, X., Ni, J., Yu, Y.: Data integrity checking with reliable data transfer for secure cloud storage. Int. J. Web Grid Serv. 14(1), 106–121 (2018)

    Article  Google Scholar 

  30. Wright, C., Kleiman, D., Sundhar, R.S.S.: Overwriting hard drive data: the great wiping controversy. In: Sekar, R., Pujari, A.K. (eds.) Information Systems Security, ICISS 2008. LNCS, vol. 5352, pp. 243–257. Springer, Heidelberg (2008)

    Google Scholar 

  31. Xue, L., Ni, J., Li, Y., Shen, J.: Provable data transfer from provable data possession and deletion in cloud storage. Comput. Stand. Interfaces 54, 46–54 (2017)

    Article  Google Scholar 

  32. Yang, C., Ye, J.: Secure and efficient fine-grained data access control scheme in cloud computing1. J. High Speed Netw. 21(4), 259–271 (2015)

    Article  Google Scholar 

  33. Yang, C., Chen, X., Xiang, Y.: Blockchain-based publicly verifiable data deletion scheme for cloud storage. J. Netw. Comput. Appl. 103, 185–193 (2018)

    Article  Google Scholar 

  34. Yang, C., Wang, J., Tao, X., Chen, X.: Publicly verifiable data transfer and deletion scheme for cloud storage. In: Naccache, D., Xu, S., Qing, S., Samarati, P., Blanc, G., Lu, R., Zhang, Z., Meddahi, A. (eds.) ICICS 2018. LNCS, vol. 11149, pp. 445–458. Springer, Heidelberg (2018)

    Google Scholar 

  35. Yang, C., Huang, Q., Li, Z., Liu, K., Hu, F.: Big Data and cloud computing: innovation opportunities and challenges. Int. J. Digit. Earth 10(1), 13–53 (2017)

    Article  Google Scholar 

Download references

Acknowledgement

This work was supported by the Open Projects of State Key Laboratory of Integrated Service Networks (ISN) of Xidian University (No. ISN19-13), the National Natural Science Foundation of Guangxi (No. 2016GXNSFAA380098) and the Science and Technology Program of Guangxi (No. AB17195045).

Author information

Authors and Affiliations

  1. State Key Laboratory of Integrated Service Networks (ISN), Xidian University, Xi’an, 710071, China

    Changsong Yang & Xiaoling Tao

  2. Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems, Guilin University of Electronic Technology, Guilin, 541004, China

    Changsong Yang & Xiaoling Tao

Authors
  1. Changsong Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoling Tao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaoling Tao .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan

    Ching-Nung Yang

  2. Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan

    Sheng-Lung Peng

  3. University of Canberra, Canberra, ACT, Australia

    Lakhmi C. Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yang, C., Tao, X. (2020). New Publicly Verifiable Cloud Data Deletion Scheme with Efficient Tracking. In: Yang, CN., Peng, SL., Jain, L. (eds) Security with Intelligent Computing and Big-data Services. SICBS 2018. Advances in Intelligent Systems and Computing, vol 895. Springer, Cham. https://doi.org/10.1007/978-3-030-16946-6_28

Download citation

Publish with us

Policies and ethics

Search

Navigation