Data Leakage Prevention

Data leakage prevention (DLP) aims to secure sensitive data by restricting unauthorized access and preventing its unintended release. Current research focuses on developing advanced DLP systems using machine learning techniques, such as statistical analysis (including TF-IDF and gradient boosting), and forecasting models to predict and prevent data breaches based on user access patterns. These methods are being applied across various domains, including healthcare, where irreversible data encoding is explored to enable data sharing while preserving privacy. The overall goal is to improve the accuracy and efficiency of DLP systems, mitigating the risks associated with data breaches and enhancing data security.