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The continuous development of new malicious codes also puts intense pressure on software and anti-virus companies to update their database definitions from time to time, which causes a challenge to keep up with the pace at which the scripts are developed and distributed (T. Liu et al., 2022) This paper puts forward an enhanced model to detect, classify, and automatically select optimal security control to respond to malicious code attacks in cloud computing environments without human supervision. The automated security control selection is essentially to keep up with the pace of malicious code development and the inevitable changing of the industrial internet to avoid the static procedures and physical human effort to secure the dynamic applications and cloud computing environments (Gergeleit et al., 2020). AWS and Azure comparison across top security scanning tools revealed that each tool has its strengths and capabilities (Singh & Aggarwal, 2022), underscoring this study's approach to automate security control selection for robust cloud security posture. 4. Figure 1 is the architectural view of how Design Science, Literature Review and Usability testing methodologies were used that were influenced by the mixed methods approach by (Jansen van Vuuren et al., 2016) The following steps provide a quick description of how the methodology was utilised to obtain the intended results: *Step 1: