The adoption of cloud computing technology has revolutionized the IT landscape, offering scalability, flexibility, and cost-efficiency. However, as organizations increasingly migrate their data and applications to the cloud, concerns about security have grown in tandem. This study presents a comprehensive analysis of cloud computing security challenges, offering a conceptual framework tailored to early adopters. The framework provides a structured approach to address security concerns, enabling organizations to harness the benefits of cloud technology while safeguarding their digital assets.

This study introduces an innovative approach, Earthquake Sentinel, utilizing Statistical Control Charts to monitor and unveil global seismic patterns. By leveraging statistical methodologies, our system aims to provide timely anomaly detection for seismic events, enabling proactive measures for risk mitigation and disaster preparedness. The methodology involves the continuous monitoring of earthquake frequency worldwide, identifying deviations from expected patterns, and triggering alerts for further investigation. Earthquake Sentinel contributes to the advancement of early warning systems, offering a valuable tool in the quest for improved global seismic risk management.