A Framework For Mitigating Security Challenges In The Cloud Using Ensemble Machine Learning
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Description
Cloud computing provides enormous prospects for almost all enterprises in the world today. Many businesses are beginning to accept these technologies in their daily operations, where employees can access their organization's resources from anywhere in the world for business continuity. However, this may raise some security concerns, particularly in the case of data breaches. Though there are pieces of research in Cloud Security, it "appears" that there is little or no attention from the research community when it comes to human factors or workforce and their relationship to cloud security threats. The emphasis is mostly on the technological aspect of information technology systems. However, it is worth noting that, while technological components are generally predictable, human factors may not be. Because human factors are ever-changing, they cannot be fully enumerated. This opens the door for attackers to infiltrate and compromise the systems using social engineering. Regardless of any technical panaceas or therapies provided, human factors remain to be an area that receives insufficient attention. Making the assumption that people will follow expected secure behavioural patterns or instincts, thereby satisfying system security expectations, may not be entirely correct. Security is not something that can be bought; human elements will always be a significant link to investigate. As a result, human factors are undeniably a big issue in cloud security. After reviewing the various literatures selected for this research, the countermeasures proposed by the various Researchers such as Sivakumaran et al .(2024) fail short of the effective ways to mitigate the threats posed by human-eccentrics variables or factors, especially most of the literature reviewed focused primarily on knowledge and skills gap as a major contributing factor to cloud security threats, but make no reference to other human factors like cognitive and behavioral patterns. And virtually all the existing countermeasures reviewed using ensemble machine learning model focused only on Insider threats, which is just one of the human factors.