Secure Data Storage and Sharing Techniques for Data Protection in Cloud Environments

Authors

  • Ms. P Sravani  PG Scholar, Department of CSE, Vemu Institute of Technology, P. Kothakota, Chittoor, Andhra Pradesh, India
  • Dr. P Nirupama  Professor & HOD, Department of CSE, Vemu Institute of Technology, P. Kothakota, Chittoor, Andhra Pradesh, India

Keywords:

Scalability, Sectors, Investment

Abstract

The cloud environment is being used by a huge number of researchers, academic institutions, government organizations, and corporations due to its minimal initial investment, maximum scalability, and a variety of other benefits. The cloud environment supports a variety of functions, but it also faces a number of challenges. The most serious issue in cloud computing and information security is data protection. To address this test, various arrangements have been made. However, because there is a lack of comprehensive research among the existing solutions, there is a need to study, classify, and analyze the significant existing work in order to investigate the applicability of these solutions to satisfy the requirements. This article provides a comparative and efficient review, as well as a top to bottom investigation of driving approaches for secure information sharing and safeguarding in the cloud environment. The discussion about each committed approach includes: working to secure the data, potential and innovative solutions in the field, important and sufficient information, such as the workflow, accomplishments, scope, gaps, future directions, and so on. In terms of each choice. Furthermore, an extensive and relative investigation of the investigated methodologies is presented. Following that, the methodologies' applicability is addressed in accordance with the requirements, and the field's research gaps and future prospects are highlighted. The authors believe that the pledge in this article will act as a motivator for the likely scientists to conduct local exploratory activity.

References

  1.  pp.1-11. https://link.springer.com/article/10.1007/s00234-021-02813-9
  2. Lo Piano, S., 2020. Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward. Humanities and Social Sciences Communications, 7(1), pp.1-7. https://www.nature.com/articles/s41599-020-0501-9
  3. Mantouka, E. (2020). Smartphone sensing for understanding driving behavior: Current practice and challenges. International Journal of Transportation Science and Technology. [online] doi: https://www.sciencedirect.com/science/article/pii/S2046043020300460
  4. Zhou, Z.H., 2021. Machine learning. Springer Nature. https://books.google.com/books?hl=en&lr=&id=ctM- EAAAQBAJ&oi=fnd&pg=PR6&dq=machine+learnin g&ots=oZPi-7Ut5s&sig=j0Tktg1FMZyeHFB6dfDaO- tGSqQ
  5. Narciso, D.A. and Martins, F.G., 2020. Application of machine learning tools for energy efficiency in industry: A review. Energy Reports, 6, pp.1181-1199. https://www.sciencedirect.com/science/article/pii/S2352484719308686
  6. Paul, A., Acar, P., Liao, W.K., Choudhary, A., Sundararaghavan, V. and Agrawal, A., 2019. Microstructure optimization with constrained design objectives using machine learning-based feedback- aware data-generation. Computational Materials Science, 160, pp.334-351. https://www.sciencedirect.com/science/article/pii/S0927025619300151

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Published

2023-10-30

Issue

Section

Research Articles

How to Cite

[1]
Ms. P Sravani, Dr. P Nirupama, " Secure Data Storage and Sharing Techniques for Data Protection in Cloud Environments" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 5, pp.165-172, September-October-2023.