Cybercrime involves illegal activities carried out by individuals who use computers, the internet, or other digital tools tocommit crimes and gain something for themselves. Cybercrime constitutes a criminal act. Cyber-attacks are becoming more frequent,and old-school methods just aren’t enough to detect or investigate them manually anymore. Machine learning is essential fordetecting cybercrimes. It has the capability to monitor, assess, and prevent cyber-attacks in order to reduce the occurrence of cybercrimes. Machine learning methods, including clustering, can play a significant role in developing a robust system for detectingcybercrime and forecasting potential cyber-attacks over time. Recent research on cybercrime includes many methods, and oneimportant technique is featuring extraction. Within this framework, a novel approach is suggested for addressing cybercrimeoffences by the elimination of certain features. The suggested method allows for the uploading of any unstructured cybercrime reportto create structured numbers using machine learning techniques. The framework should provide a full report on how oftencybercrimes occur, how serious they are, and how they are classified and solved. The function summary comes from using textmining, performance measures, and analysis to forecast cybercrime activity.Keywords: SaaS applications are deployed through cloud computing environments, benefiting from virtualization technologies andscalable cloud architecture to support efficient, large-scale software deployment