Skip to main content
SpringerLink
Log in

Performance Analysis of Cloud Data Verification Using MD5 and ECDSA Method

  • Conference paper
  • First Online:
Data Science and Analytics (REDSET 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 799))

Abstract

Cloud computing enable the users to outsource and access data economically using storage as a service. In this storage model, the data owner doesnot have any control of the data once its stores on cloud server. Therefore, privacy and security of the data is a challenging issue in cloud computing. To provide the integrity of the outsourced data, we have proposed a lightweight data auditing technique such as MD5 and ECDSA signature method using third party auditor. The result analysis of the proposed method shows that, ECDSA has better security performance than the computation as compared to MD5 method for larger data size. The selection of the signature method depends on the priority of the data size and frequency of accessing.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Liu, J., Huang, K., Rong, H., Wang, H., Xian, M.: Privacy-preserving public auditing for regenerating-code-based cloud storage. IEEE Trans. Inf. Forensics Secur. 10(7), 1513–1528 (2015)

    Article  Google Scholar 

  2. Zhu, Y., Hu, H., Ahn, G.J., Yu, M.: Cooperative provable data possession for integrity verification in multicloud storage. IEEE Trans. Parallen Distrib. Syst. 23(12), 2231–2244 (2012)

    Article  Google Scholar 

  3. Wang, H., He, D., Tang, S.: Identity-based distributed provable data possession in multi-cloud storage. IEEE Trans. Inf. Forensics Secur. 11(6), 1165–1176 (2016)

    Article  Google Scholar 

  4. Yu, Y., Au, M., Ateniese, G., Huang, X., Susilo, W., Dai, Y., Min, G.: Identity-based remote data integrity checking with perfect data privacy preserving for cloud storage. IEEE Trans. Inf. Forensics Secur. 12(4), 767–778 (2017)

    Article  Google Scholar 

  5. Yang, L., Xia, L.: An efficient and secure public batch auditing protocol for dynamic cloud storage data. In: IEEE International Computer Symposium, pp. 671–675 (2016)

    Google Scholar 

  6. Wang, Y., Wu, Q., Qin, B., Shi, W., Deng, R.H., Hu, J.: Identitybased data outsourcing with comprehensive auditing in clouds. IEEE Trans. Inf. Forensics Secur. 12(4), 940–952 (2017)

    Article  Google Scholar 

  7. Zhang, Y., Xu, C., Liang, X., Li, H., Mu, Y., Zhang, X.: Efficient public verification of data integrity for cloud storage systems from indistinguishability obfuscation. IEEE Trans. Inf. Forensics Secur. 12(3), 676–688 (2017)

    Article  Google Scholar 

  8. Bellare, M., Canetti, R., Krawczyk, H.: Keying hash functions for message authentication. In: International Cryptology Conference on Advances in Cryptology (CRYPTO 1996), pp. 1–15 (1996)

    Google Scholar 

  9. Wang, B., Li, B., Li, H.: Oruta: privacy-preserving public auditing for shared data in the cloud. IEEE Tran. Cloud Comput. 2, 43–56 (2014)

    Article  Google Scholar 

  10. Yang, K., Jia, X.: An efficient and secure dynamic auditing protocol for data storage in cloud computing. IEEE Trans. Parallel Distrib. Syst. 24(9), 1717–1726 (2013)

    Article  Google Scholar 

  11. Chauhan, M.M.: An implemented of hybrid cryptography using elliptic curve cryptosystem (ECC) and MD5. In: IEEE International Conference on Inventive Computation Technologies (ICICT), vol. 3, pp. 1–6 (2016)

    Google Scholar 

  12. Indrayani, R., Nugroho, H.A., Hidayat, R., Pratama, I.: Increasing the security of MP3 steganography using AES encryption and MD5 hash function. In: IEEE 2nd International Conference on Science and Technology-Computer (ICST), pp. 129–132 (2016)

    Google Scholar 

  13. Zhong, L., Wan, W., Kong, D.: Javaweb login authentication based on improved MD5 algorithm. In: IEEE International Conference on Audio, Language and Image Processing (ICALIP), vol. 3, pp. 131–135 (2016)

    Google Scholar 

  14. van Rijswijk-Deij, R., Jonker, M., Sperotto, A.: On the adoption of the elliptic curve digital signature algorithm (ECDSA) in DNSSEC. In: IEEE 12th International Conference on Network and Service Management (CNSM), pp. 258–262 (2016)

    Google Scholar 

  15. Li, H., Zhang, R., Yi, J., Lv, H.: A novel algorithm for scalar multiplication in ECDSA. In: IEEE International Conference on Computational and Information Sciences, pp. 943–946 (2013)

    Google Scholar 

  16. van Rijswijk-Deij, R., Hageman, K., Sperotto, A., Pras, A.: The performance impact of elliptic curve cryptography on DNSSEC validation. IEEEACM Trans. Netw. 25(2), 738–750 (2017)

    Article  Google Scholar 

  17. Kneevi, M., Nikov, V., Rombouts, P.: Low-latency ECDSA signature verificationa road toward safer traffic. IEEE Trans. Very Large Scale Integr. VLSI Syst. 24(11), 3257–3267 (2016)

    Article  Google Scholar 

  18. Yalin, T.: Compact ECDSA engine for IoT applications. IEEE Electron. Lett. 52(15), 1310–1312 (2016)

    Article  Google Scholar 

  19. Redondo, J.M., Ortin, F.: A comprehensive evaluation of common python implementations. IEEE Softw. 32(4), 76–84 (2015)

    Article  Google Scholar 

  20. Sun, D., Fu, M., Zhu, L., Li, G., Lu, Q.: Nonintrusive anomaly detection with streaming performance metrics and logs for DevOps in public clouds: a case study in AWS. IEEE Trans. Emerg. Topics Comput. 4(2), 278–289 (2016)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Science Engineering, University of Petroleum and Energy Studies, Dehradun, India

    G. L. Prakash, Manish Prateek & Inder Singh

Authors
  1. G. L. Prakash
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manish Prateek
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Inder Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to G. L. Prakash .

Editor information

Editors and Affiliations

  1. University of Arkansas, Fayetteville, AR, USA

    Brajendra Panda

  2. GD Goenka University, Gurugram, Haryana, India

    Sudeep Sharma

  3. GD Goenka University, Gurugram, Haryana, India

    Nihar Ranjan Roy

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Prakash, G.L., Prateek, M., Singh, I. (2018). Performance Analysis of Cloud Data Verification Using MD5 and ECDSA Method. In: Panda, B., Sharma, S., Roy, N. (eds) Data Science and Analytics. REDSET 2017. Communications in Computer and Information Science, vol 799. Springer, Singapore. https://doi.org/10.1007/978-981-10-8527-7_52

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-8527-7_52

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8526-0

  • Online ISBN: 978-981-10-8527-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation