Skip to main content
SpringerLink
Log in

PPSecS: Privacy-Preserving Secure Big Data Storage in a Cloud Environment

  • Research Article-Computer Engineering and Computer Science
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

The proliferation of social networks, the Internet of Things, and economic mobility has led to an exponential increase in data. New data having high volume, high velocity, high variety, and high value are called big data. Big data present additional requirements in terms of storage and computation resources. Various enterprises aim to outsource their big data services to the cloud because of its cost efficiency, less management, resource pooling, and resilient computing. However, outsourcing the storage of sensitive data can expose them to potential security risks. Encryption presents a straightforward solution for data privacy preserving. In traditional encryption mechanisms, such as advanced encryption standard, the data owner and users must share an exact key for both data encryption and decryption. Currently, these mechanisms do not provide a scalable and secure solution for big data storage and analysis. Furthermore, they need to be more efficient to support big data velocity. Unfortunately, securing outsourced big data storage to a public cloud environment to later maintain efficient and secure processing over encrypted data by cloud servers cannot be ensured using traditional encryption mechanisms. In this paper, we propose a security approach for this issue by which honest but curious users or cloud service providers cannot reach complete information from the stored data. From the analysis, the proposed approach can provide secure cloud-assisted big data. Meanwhile, the performance evaluation shows the efficiency of the proposed approach.

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
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Availability of data

The tool used to generate the datasets used in this article is publicly available and the link for this tool is presented in the reference section.

References

  1. The premier global market intelligence firm.

  2. Alhazmi, H.E.; Eassa, F.E.; Sandokji, S.M.: Towards big data security framework by leveraging fragmentation and blockchain technology. IEEE Access 10, 10768–10782 (2022)

    Article  Google Scholar 

  3. Aljawarneh, S.; Yassein, M.B.; Talafha, W.A.: A resource-efficient encryption algorithm for multimedia big data. Multimedia Tools and Applications 76, 22703–22724 (2017)

    Article  Google Scholar 

  4. Awaysheh, F.M.; Aladwan, M.N.; Alazab, M.; Alawadi, S.; Cabaleiro, J.C.; Pena, T.F.: Security by design for big data frameworks over cloud computing. IEEE Trans. Eng. Manage. 69(6), 3676–3693 (2022)

    Article  Google Scholar 

  5. Berisha, B.; Mëziu, E.; Shabani, I.: Big data analytics in cloud computing: an overview. J. Cloud Comput, 11(1), (2022).

  6. Bernstein; Daniel J.: The Salsa20 Family of Stream Ciphers, pages 84–97. Springer Berlin Heidelberg, Berlin, Heidelberg, (2008).

  7. Bhuvaneswari, V.: Role of big data analytics in industrial revolution 4.0. In: Big Data Applications in Industry 4.0, pages 85–105. Auerbach Publications, (2022).

  8. Chaudhary, Y.; Pathak,H.: Security of big data: Threats and different approaches towards big data security. In Dharma P. Agrawal, Nadia Nedjah, B. B. Gupta, and Gregorio Martinez Perez, editors, Cyber Security, Privacy and Networking, pages 357–368, Singapore, (2022). Springer Nature Singapore.

  9. Cheng, H.; Rong, C.; Hwang, K.; Wang, W.; Li, Y.: Secure big data storage and sharing scheme for cloud tenants. China Communications 12(6), 106–115 (2015)

    Article  Google Scholar 

  10. Das, M.; Dash, R.: Role of cloud computing for big data: a review. In: Intelligent and Cloud Computing, pages 171–179, Singapore, (2021). Springer Singapore.

  11. Daskevics, A.; Nikiforova, A.: Iotse-based open database vulnerability inspection in three baltic countries: Shobevodsdt sees you. In: 2021 8th International Conference on Internet of Things: Systems, Management and Security (IOTSMS), pages 1–8. IEEE, (2021).

  12. Devmane, V.; Lande, B.K.; Joglekar, J.; Hiran, D: Preserving data security in cloud environment using an adaptive homomorphic blockchain technique. Arab. J. Sci. Eng. pages 1–14, (2022).

  13. Rydning, D.R.J.G.J.: The digitization of the world from edge to core - seagate technology, (2018) [Online].

  14. Tamer, E.; Huang, Z.; Zhexue, J.; Rrplib, : A spark library for representing hdfs blocks as a set of random sample data blocks. Sci. Comput. Program. 184, 102301 (2019)

  15. Gai, K.; Qiu, M.; Zhao, H.: Security-aware efficient mass distributed storage approach for cloud systems in big data. In: 2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS), pages 140–145, (2016).

  16. Guan, S.; Zhang, C.; Wang, Y.; Liu, Y.: Hadoop-based secure storage solution for big data in cloud computing environment. Dig. Commun. Netw. (2023).

  17. Heys, H.M.; Tavares, S.E.: Avalanche characteristics of substitution-permutation encryption networks. IEEE Trans. Comput. 44(9), 1131–1139 (1995)

    Article  Google Scholar 

  18. Hudaib, A.; Alnabhan, M.; Harfoushi, O.; Obiedat, R.; Adwan, O.; Adham, W.: Emerging trends of outsourcing business to cloud computing services: a perspective study. Commun. Netw, 2014, (2014).

  19. Kaluarachchi, Y.: Implementing data-driven smart city applications for future cities. Smart Cities 5(2), 455–474 (2022)

    Article  Google Scholar 

  20. Trung, L.; Phan, K.; Hung, D.; Ha My, K.: The connection of iot to big data–hadoop ecosystem in a digital age. In: Emerging Technologies in Data Mining and Information Security, pages 571–580, Singapore, (2021). Springer Nature Singapore.

  21. Lai, X.: On the design and security of block ciphers. PhD thesis, ETH Zurich, (1992).

  22. 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  ADS  Google Scholar 

  23. Liu, J.; Sun, B.; Li, C.: Design and cryptanalysis of a new iterative structure. IET Information Security, (2022).

  24. McAfee, A.; Brynjolfsson, E.; Davenport, T.H.; Patil, D.J.; Barton, D.: Big data: the management revolution. Harv. Bus. Rev. 90(10), 60–68 (2012)

    PubMed  Google Scholar 

  25. Nafis Md, T.; Biswas, R.: A secure technique for unstructured big data using clustering method. Int. J. Inform. Technol. pages 1–12, (2019).

  26. Narayanan, U.; Paul, V.; Joseph, S.: A novel system architecture for secure authentication and data sharing in cloud enabled big data environment. J. King Saud. Univ.-Comput. Inform. Sci. 34, 3121–3135 (2022)

    Google Scholar 

  27. Narayanan, U.; Paul, V.; Joseph, S.: A novel system architecture for secure authentication and data sharing in cloud enabled big data environment. Journal of King Saud University-Computer and Information Sciences 34(6), 3121–3135 (2022)

    Article  Google Scholar 

  28. Peng, J.; Xu, H.; Song, J.: Hrse: A novel high-speed random sampling encryption scheme on big data. In: 2021 IEEE 15th International Conference on Big Data Science and Engineering (BigDataSE), pages 57–64, (2021).

  29. Kavin, B.P.; Ganapathy, S.; Kanimozhi, U.; Kannan, A.: An enhanced security framework for secured data storage and communications in cloud using ecc, access control and ldsa. Wirel. Pers. Commun. 115(2), 1107–1135 (2020)

    Article  Google Scholar 

  30. Qin, P.; Li, W.; Ding, K.; Lakshmanna, K.: A big data security architecture based on blockchain and trusted data cloud center. Wirel. Commun. Mob. Comput., (2022).

  31. Rajan, S.; Ginkel, W.; Sundaresan, N.; Bardhan, A.; Chen,Y.; Fuchs, A.; Kapre, A.; Lane, A.; Lu, R.; Manadhata, P.; Molina, J.; Cardenas, A.; Murthy, P.; Roy, A.; Sathyadevan, S.; Shah, V.: Cloud security alliance report on the top ten challenges in big data privacy and security. Technical report, Cloud Security Alliance, 04 2013.

  32. Naik, M.; Madala, R.; Rao, S.; Cheng, W.; Bidare Divakarachari, L.; Parameshachari., Ananda Babu, J.; Kivudujogappa Lingappa, H.: An efficient and secure big data storage in cloud environment by using triple data encryption standard. Big Data and Cognitive Comput., 6(4):101, (2022).

  33. Ramachandra, M.N.; Srinivasa Rao, M.; Lai, W.C.; Parameshachari, B.D.; Ananda Babu, J.; Hemalatha, K.L.: An efficient and secure big data storage in cloud environment by using triple data encryption standard. Big Data and Cognitive Comput. 6(4), (2022).

  34. Rawat, D.B.; Doku, R.; Garuba, M.: Cybersecurity in big data era: From securing big data to data-driven security. IEEE Trans. Serv. Comput. 14(6), 2055–2072 (2019)

    Article  Google Scholar 

  35. Bethencourt, J.; Sahai, A.; Waters, B.: Fuzzy identity-based encryption. In: Advances in Cryptology – EUROCRYPT 2005, pages 457–473, Berlin, Heidelberg, (2005). Springer Berlin Heidelberg.

  36. Salloum, S.; Huang, J.Z.; He, Y.: Random sample partition: A distributed data model for big data analysis. IEEE Trans. Industr. Inf. 15(11), 5846–5854 (2019)

    Article  Google Scholar 

  37. Strohbach, M.; Daubert, J.; Ravkin, H.; Lischka, M.: Big Data Storage, pages 119–141. Springer International Publishing, Cham, (2016).

  38. Tajammul, M.; Shaw, R. N.; Ghosh, A.; Parveen, R.: Error Detection Algorithm for Cloud Outsourced Big Data, pages 105–116. Springer Singapore, Singapore, (2021).

  39. Josephine Usha Lawrance and Jesu Vedha Nayahi Jesudhasan: Privacy preserving parallel clustering based anonymization for big data using mapreduce framework. Appl. Artif. Intell. 35(15), 1587–1620 (2021)

  40. Vaudenay, S.: On the lai-massey scheme. In: International Conference on the Theory and Application of Cryptology and Information Security, pages 8–19. Springer, (1999).

  41. Viriyasitavat, W.; Da Li, X.; Sapsomboon, A.; Dhiman, G.; Hoonsopon, D.: Building trust of blockchain-based internet-of-thing services using public key infrastructure. Enterprise Information Systems 16(12), 2037162 (2022)

    Article  Google Scholar 

  42. Walonoski, J.; Kramer, M.; Nichols, J.; Quina, A.; Moesel, C.; Hall, D.; Duffett, C.; Dube, K.; Gallagher, T.; McLachlan. Synthea, S.: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record. J. Am. Med. Inform. Assoc. 25(3), 230–238 (2017) 8

    Article  PubMed Central  Google Scholar 

  43. Haiyang, Yu.; Li, H.; Yang, X.; Ma, H.: On distributed object storage architecture based on mimic defense. China Communications 18(8), 109–120 (2021)

    Article  Google Scholar 

  44. Zhang, Y.; Yang, M.; Zheng, D.; Lang, P.; Axin, W.; Chen, C.: Efficient and secure big data storage system with leakage resilience in cloud computing. Soft. Comput. 22(23), 7763–7772 (2018)

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable feedback for improving the quality of this manuscript.

Funding

The authors declare that this work is presented without any kind of funding.

Author information

Authors and Affiliations

  1. LIRE laboratory, Software Technology and Information Systems Department, University of Constantine 2 - Abdelhamid Mehri, Nouvelle ville Ali Mendjli, BP:67A, Constantine, Algeria

    Imene Bouleghlimat, Souheila Boudouda & Salima Hacini

Authors
  1. Imene Bouleghlimat
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Souheila Boudouda
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Salima Hacini
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Imene Bouleghlimat was responsible for conceptualization, methodology, and writing—original draft preparation; Imene Bouleghlimat, Souheila Boudouda, and Salima Hacini were involved in writing—reviewing and editing; and Souheila Boudouda and Salima Hacini contributed to supervision.

Corresponding author

Correspondence to Imene Bouleghlimat.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bouleghlimat, I., Boudouda, S. & Hacini, S. PPSecS: Privacy-Preserving Secure Big Data Storage in a Cloud Environment. Arab J Sci Eng 49, 3225–3239 (2024). https://doi.org/10.1007/s13369-023-07924-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-023-07924-4

Keywords

Search

Navigation