PRISMA Archetype-Based Systematic Literature Review of Security Algorithms in the Cloud
John Kwao Dawson, Frimpong Twum, James Benjamin Hayfron Acquah, Yaw Marfo Missah
Abstract
Industries have embraced cloud computing for their daily operations due to the volume of data they create. As data generation and consumption have increased, the challenges and opportunities have also increased. Researchers have proposed various cryptographic schemes to secure data on the cloud. Regardless of the multiple cryptographic schemes proposed, security remains an obstacle to cloud computing’s widespread adoption. Also, these cryptographic schemes’ run times are proportional to data sizes, motivating excessive CPU engagement during execution of huge data, which has consequences for the need for high bandwidth to transfer data to the cloud. This systematic review tries to uncover the most often used cryptographic schemes and their run time trends to attain confidentiality and privacy of cloud data. The study considered published articles from well-known databases such as Taylor & Francis, Scopus, Research Gate, Web of Science, IEEE Xplore, Science Direct, Hindawi, Google Scholar, Sage, Emerald, Wiley Online Library, and ACM from 2016 to 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to select 73 published works for this study using keyword searching. Data security and cloud security were the security challenges that received the greatest attention in the study with encryption techniques as the most common solution. From the study, 90% of the schemes used to secure data on the cloud produced linear run times. The investigation discovered that nonlinear symmetric stream cipher methods were infrequently employed to protect the secrecy and privacy of cloud data.