Cloud-Based Data Governance: Ensuring Security, Compliance, and Privacy

Main Article Content

Shivali Naik

Abstract

Cloud computing has been taken up very rapidly and has over time changed the way an organization stores, processes, and shares data towards much higher levels of efficiency, scalability, and innovation. This paradigm shift, however, bears its unique and very complex challenges towards security of data and network security. Since sensitive in- formation finds its storage and transmission increasingly on shared multi- tenant cloud environments, the potential for data breaches, unauthorized access, and other cyber threats becomes much more viable. Moreover, the shared responsibility model in real. A further layer of complexity is added to cloud computing by necessitating providers and consumers to implement robust security measures. In this chapter, the most current strategies, technologies, and frameworks that can be used to secure data and networks within cloud environments will be discussed. Challenges will be considered that will provide a rational basis for achieving the appropriate level of assurance in the security of information systems and, as a consequence, the data they process, against confidentiality, integrity, and availability threats to evolve cyber threats. This will allow the organization to take full advantage of cloud computing, keeping compliance and information confidential and resilient against ever-changing cyber threats.

Article Details

How to Cite
Naik, S. (2023). Cloud-Based Data Governance: Ensuring Security, Compliance, and Privacy. The Eastasouth Journal of Information System and Computer Science, 1(01), 69–87. https://doi.org/10.58812/esiscs.v1i01.452
Section
Articles

References

D. Dayton and J. Eipe, “Introduction to Snowflake,” in Snowflake Recipes: A Problem-Solution Approach to Implementing Modern Data Pipelines, Springer, 2024, pp. 1–22.

M. Talha, M. Sohail, and H. Hajji, “Analysis of research on amazon AWS cloud computing seller data security,” Int. J. Res. Eng. Innov., vol. 4, no. 3, pp. 131–136, 2020.

V. Shah, “Novel Approach For Analyzing Intraday Stock Market Behavior Using Stream Data Analytics”.

H. Shukur, S. Zeebaree, R. Zebari, D. Zeebaree, O. Ahmed, and A. Salih, “Cloud computing virtualization of resources allocation for distributed systems,” J. Appl. Sci. Technol. Trends, vol. 1, no. 2, pp. 98–105, 2020.

B. Alouffi, M. Hasnain, A. Alharbi, W. Alosaimi, H. Alyami, and M. Ayaz, “A systematic literature review on cloud computing security: threats and mitigation strategies,” Ieee Access, vol. 9, pp. 57792–57807, 2021.

A. K. Sandhu, “Big data with cloud computing: Discussions and challenges,” Big Data Min. Anal., vol. 5, no. 1, pp. 32–40, 2021.

D. A. Shafiq, N. Z. Jhanjhi, A. Abdullah, and M. A. Alzain, “A load balancing algorithm for the data centres to optimize cloud computing applications,” IEEE Access, vol. 9, pp. 41731–41744, 2021.

P. Sun, “Security and privacy protection in cloud computing: Discussions and challenges,” J. Netw. Comput. Appl., vol. 160, p. 102642, 2020.

M. M. Sadeeq, N. M. Abdulkareem, S. R. M. Zeebaree, D. M. Ahmed, A. S. Sami, and R. R. Zebari, “IoT and Cloud computing issues, challenges and opportunities: A review,” Qubahan Acad. J., vol. 1, no. 2, pp. 1–7, 2021.

J. Alonso et al., “Understanding the challenges and novel architectural models of multi-cloud native applications–a systematic literature review,” J. Cloud Comput., vol. 12, no. 1, p. 6, 2023.