A cyber bullying detection system is a technological solution that aims to identify and prevent instances of cyberbullying in online platforms and social media. The system employs various techniques such as natural language processing (NLP), machine learning, user profiling,social network analysis and image analysis to analyze user-generated content and detect patterns or indicators of cyberbullying behavior. It collects data from different sources, preprocesses it, and uses NLP to understand and analyze textual content. Machine learning algorithms are trained on labeled datasets to classify content as cyberbullying or non-cyberbullying. User profiling helps in understanding individual behavior, while social network analysis identifies networks or groups involved in cyberbullying. The system can also analyze images and multimedia content for offensive or harmful material.Real-time monitoring and reporting mechanisms enable prompt intervention and human moderation is necessary forfinal judgments and actions. While cyber bullying detection systems are not foolproof, they provide valuable tools for identifying and addressing cyberbullying incidents to create safer online environment.