Data Leakage Detection Using ML

Data Leakage is one of the major problems faced by the authorities of the corporate society. Data Leakage could be of different types such as Malicious insiders, Physical exposure, electronic communication, and Accidental leakage. The most common out of all these above -listed types is accidental leakage i.e., data leak due to human error. There have been several incidents regarding data leakage in different companies across the world. And so, our goal in this project is to achieve a solution to prevent data leakage through Machine Learning. However, the detection techs available cannot provide any absolute protection as of now. Thus, it is very essential to find a solution to this risky problem as soon as possible. This research aims to design and implement a data leakage detection system based on machine learning. Furthermore, applying the synthetic minority oversampling technique (SMOTE) is one option to overcome this imbalance problem. Known machine learning methods are regarded as one of the most effective approaches to find instances of data leaking.