A Systematic Literature Review on Risk Assessment in Cloud Computing: Recent Research Advancements - Saadia Drissi; Meriyem Chergui; Zakaria Khatar (IEEE Access)
The era of Industry 4.0 is characterized by a significant shift in information and communication technology, which has facilitated the emergence of new technology-driven investments. Key components such as Cloud Computing, Artificial Intelligence (AI), Big Data, and the Internet of Things (IoT) form the foundation of this industrial revolution. Cloud Computing serves as a service offering organizations a range of opportunities such as flexibility, scalability, and cost-effectiveness. However, it is essential for organizations to guarantee the security of their resources, especially applications, data, and cloud-based networks to use all cloud offered services effectively for both individuals and organizations. Risk assessment (RA) is essential for identifying, analyzing, and evaluating potential risks that could negatively impact cloud resources, yet developing a tailored approach continues to be challenging, because of the complex nature of cloud. The objective of this systematic literature review is to thoroughly examine the latest advancements in cloud computing security, with a primary focus on RA. Our study explores also various cloud RA scenarios where Machine Learning (ML) and Deep Learning (DL) techniques are applied to identify and mitigate potential risks in cloud environments. This study highlights the latest proposed solutions for assessing risks on cloud, thereby contributing to the development of a comprehensive RA while addressing the specific characteristics of the cloud and its complex nature. Additionally, it addresses process for future research work to enhance RA according many criteria.