@article {10.3844/jcssp.2020.1625.1638,
article_type = {journal},
title = {Computational and Statistical Analysis of Security and Privacy Parameters of Cloud Computing in Information Technology},
author = {Claver, Jimbo and Hamraz, Edris and Suzuki, Takeru and Seraphin, Ngongo and Gabriel, Andjiga and Magloire, Etoua},
volume = {16},
number = {11},
year = {2020},
month = {Nov},
pages = {1625-1638},
doi = {10.3844/jcssp.2020.1625.1638},
url = {https://thescipub.com/abstract/jcssp.2020.1625.1638},
abstract = {Information Technology has transformed the way cloud computing itself can help to manage, consume and improve cost efficiencies, accelerate innovation, provide faster time to the market and develop the ability to scale applications on demands and services. In this research work, we present recent developments and some statistical analysis techniques used in cloud computing development with challenges related to the security and privacy in information technology. The ultimate goal in this research is to detect relevant factors that are more likely to affect security and privacy in cloud computing services. Moreover, we identify the security risks and the threats that have already been recognized by cloud security alliance as vital components of those challenges. Finally, the solutions we found in this study will efficiently help private and governmental organizations to resolve some of the important security challenges. Although the suggested solutions still remain at the Service level agreements contracted between the cloud provider and consumer, it will secure the cloud users and earn their satisfactions in cloud computing services.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}