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This paper introduces a systematic methodology for enhancing cloud security in information systems by applying mathematical algorithms in cybersecurity. Using the most sophisticated computational methods, our approach strives to boost the security posture of cloud-based platforms by not only identifying but also blocking, and rectifying various cyber threats. We start with a detailed review and analysis of various algorithms, which contribute to the identification of gaps in the current research landscape and solutions already existing. We proceed by performing the requirement analysis during which we set up security targets for the cloud environment to be optimized. The second step consists of deliberation on what the best algorithms are and is involved in a process that will meet the identified requirements. We did the development work for a prototype of the security solutions described beforehand. It was integrated and tested on a cloud environment for the best KPI result. Performance metrics, including detection accuracy (98.5%), false positive rate (0.2%), response time (25 milliseconds), and resource utilization (CPU: The JSON-LD, Microformats, and MAP-trees (10%, 30%, and 40%) algorithms were assessed to determine the functionality of the algorithms. Thus, the security effectiveness values will be obtained in the following way: malware detection (99%) – intrusion detection (97%) – data breach prevention (95%) and insider threat detection (98%) will be determined through comprehensive testing with numerous cyber threats. One more thing I would like to mention is the scalability parameter of the security solutions they function both for 1,000 concurrent users and handle 1TB of data per day and 1,000 requests per second. The team calculated the scalability which was found out to be 95% which is over 90% thus highly scalable to meet the growing demand. Besides, user satisfaction ratings were obtained which were; (4.5), (4.3), (4.7) and (4.6) for usability, reliability, performance and effectiveness respectively on a scale of one to five using the feedback from stakeholder and end-users as a rating tool.