Secure Persona Detection and Data Leakage Prevention System Using Machine Learning

In the time where data breaches are increasing, the need for advanced security systems have become more important. This project provides an enhanced machine learning-based system designed for security measures by applying a multi-layered approach to detect user personas and prevent data leakage. At its core, the system uses various Machine Learning models such as Random Forest classifier combined with deep learning techniques to analyse complex behavioural and transactional data. This integration allows for more enhanced detection of user personas, adapting dynamically to increasing security threats. Further advancements include the implementation of real-time data processing and anomaly detection algorithms that monitor data for unusual patterns, alerting potential breaches before they occur. The project also incorporates encryption protocols and ensure the integrity and confidentiality of sensitive data across various networks. The project extends beyond traditional security measures by using predictive analytics to forecast potential security lapses, enabling appropriate action. This approach ensures a robust defence mechanism against cyber threats, significantly enhancing organizational security postures.