Skip to main content
SpringerLink
Log in

A data security and integrity framework using third-party cloud auditing

  • Original Research
  • Published:
International Journal of Information Technology Aims and scope Submit manuscript

Abstract

In the current cloud computing development era, security and integrity restrictions on the users and service providers are at a constant increase. Users using cloud storage enjoy remote data storage with high-quality on-demand applications and services but at the cost of local data storage and maintenance burden. Lack of data integrity protection is the main reason causing difficulty in physical possession of the user’s outsourced data. The main setback behind this lack of integrity is the need for a clear-cut cloud computing public audibility for cloud data storage, wherein the users assign a third-party auditor to check for the integrity of outsourced data. The aim  of this paper is to suggest an efficient cloud storage system with security restrictions using the Hadoop framework, centering on Apache Ambari. To demonstrate, a five-stage security check framework is proposed with the Kerberos protocol, Knox API, Apache Ranger, and encryption techniques are deployed in a single framework i.e., Apache Ambari. Ambari framework is used to enable those techniques to provide multi-layered protection for the data stored in the Hadoop distributed file system. The results prove that the proposed four-stage security framework effectively increases the data integrity of the cloud users.

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

Similar content being viewed by others

References

  1. Voorsluys W, Broberg J, Buyya R (2011) Cloud computing principles and paradigms. Wiley, Hoboken

    Google Scholar 

  2. Shawish A, Salama M (2014) Cloud computing: paradigms and technologies. Springer, Berlin, pp 67–39

    Google Scholar 

  3. Diwaker C, Dembla P (2014) Survey on cloud computing. Int J Adv Res Comput Sci 5(5)

  4. Deepa R, Dheeba J (2019) Resource allocation in cloud computing for energy efficiency. Int J Eng Adv Technol (IJEAT). 8(6)

  5. Mthunzi SN, Benkhelifa E, Bosakowski T, Guegan CG, Barhamgi M (2020) Cloud computing security taxonomy: from an atomistic to a holistic view. Future Gener Comput Syst 107:620–644

    Article  Google Scholar 

  6. Coppolino L, D’Antonio S, Mazzeo G, Romano L (2017) Cloud security: emerging threats and current solutions. Comput Electr Eng 59:126–140

    Article  Google Scholar 

  7. Garg N, Bawa S (2016) Comparative analysis of cloud data integrity auditing protocols. J Netw Comput Appl 66:17–32

    Article  Google Scholar 

  8. Shaikh AH, Meshram BB (2021) Security issues in cloud computing. In: Intelligent computing and networking. Springer, Singapore, pp. 63–77

  9. Singh A, Chatterjee K (2017) Cloud security issues and challenges: a survey. J Netw Comput Appl 79:88–115

    Article  Google Scholar 

  10. Shen J, Shen J, Chen X, Huang X, Susilo W (2017) An efficient public auditing protocol with novel dynamic structure for cloud data. IEEE Trans Inf Forensics Secur 12(10):2402–2415

    Article  Google Scholar 

  11. Tunc C, Hariri S, Merzouki M, Mahmoudi C, De Vaulx FJ, Chbili J, Battou A (2017) Cloud security automation framework. In: 2017 IEEE 2nd international workshops on foundations and applications of self* systems (FAS* W). IEEE, pp. 307–312

  12. Li Y, Yua Y, Yang B, Min G, Wu H (2016) Privacy preserving cloud data auditing with efficient key update 0167–739X/©. Elsevier, Amsterdam

    Google Scholar 

  13. Alam T (2020) Cloud computing and its role in the information technology. IAIC Trans Sustain Digit Innov (ITSDI) 1(2):108–115

    Article  Google Scholar 

  14. Abdullah S, Bakar KAA (2018) Security and privacy challenges in cloud computing. In: 2018 Cyber resilience conference (CRC). IEEE, pp. 1–3

  15. Coppolino L, D’Antonio S, Mazzeo G, Romano L (2016) Cloud security: emerging threats and current solutions 0045–7906/©. Elsevier Ltd, Amsterdam

    Google Scholar 

  16. Venkatraman K, Geetha K (2019) Dynamic virtual cluster cloud security using hybrid steganographic image authentication algorithm. Automatika 60(3):314–321. https://doi.org/10.1080/00051144.2019.1624409

    Article  Google Scholar 

  17. Majumdar S, Madi T, Wang Y, Jarraya Y, Pourzandi M, Wang L, Debbabi M (2017) User-level runtime security auditing for the cloud. IEEE Trans Inf Forensics Secur 13(5):1185–1199

    Article  Google Scholar 

  18. Worku SG, Xu C, Zhao J, He X (2014) Secure and efficient privacy-preserving public auditing scheme for cloud storage. Comput Electr Eng 40(5):1703–1713

    Article  Google Scholar 

  19. Aljawarneh SA, Yassein MOB (2016) A conceptual security framework for cloud computing issues. Int J Intell Inf Technol (IJIIT) 12(2):12–24

    Article  Google Scholar 

  20. Mall S, Saroj SK (2018) A new security framework for cloud data. Proc Comput Sci 143:765–775

    Article  Google Scholar 

  21. Zhao J, Wang L, Tao J, Chen J, Sun W, Ranjan R, Georgakopoulos D (2014) A security framework in G-Hadoop for big data computing across distributed Cloud data centres. J Comput Syst Sci 80(5):994–1007

    Article  MathSciNet  Google Scholar 

  22. Sirohi P, Agarwal A (2015) Cloud computing data storage security framework relating to data integrity, privacy and trust. In: 2015 1St international conference on next generation computing technologies (NGCT). IEEE, pp. 115–118

  23. Chang V, Ramachandran M (2015) Towards achieving data security with the cloud computing adoption framework. IEEE Trans Serv Comput 9(1):138–151

    Article  Google Scholar 

  24. Jouini M, Rabai LBA (2019) A security framework for secure cloud computing environments. In: Cloud security: concepts, methodologies, tools, and applications. IGI Global, pp. 249–263

  25. Chang V, Kuo YH, Ramachandran M (2016) Cloud computing adoption framework: a security framework for business clouds. Future Gener Comput Syst 57:24–41

    Article  Google Scholar 

  26. Balusamy B, Venkatakrishna P, Vaidhyanathan A, Ravikumar M, Munisamy ND (2015. Enhanced security framework for data integrity using third-party auditing in the cloud system. In: Artificial intelligence and evolutionary algorithms in engineering systems. Springer, New Delhi. pp. 25–31

Download references

Funding

Not applicable.

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

    B. Mishachandar, S. Vairamuthu & M. Pavithra

Authors
  1. B. Mishachandar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Vairamuthu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. Pavithra
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. Vairamuthu.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interest regarding the publication of this article.

Data availability

Not applicable.

Code availability

Not applicable.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mishachandar, B., Vairamuthu, S. & Pavithra, M. A data security and integrity framework using third-party cloud auditing. Int. j. inf. tecnol. 13, 2081–2089 (2021). https://doi.org/10.1007/s41870-021-00738-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41870-021-00738-3

Keywords

Search

Navigation