Survey on Data Leakage Prevention through Machine Learning Algorithms
Er. Garima Agrawal, Samta Jaın Goyal · 2022 International Mobile and Embedded Technology Conference (MECON) · 2022
As the Internet develops and network data transmission keeps on expanding, managers are confronted with the errand of holding private data back from leaving their organizations. In different information leakage cases, information misfortune is caused mostly by human missteps. Currently government associations show that the quantities of information leakage occasions have developed rapidly. One of the significant issues in the data security research is information spillage or information misfortune particularly brought about by insider danger as insider dangers can possibly deliver serious harm to the association’s assets, monetary resources and notoriety. Therefore protection and suspection of data detection can restrict the associations from willing to share the information from one another and this is one of the significant errands in the data security. In this paper, we study various literatures showing mitigation of data leakage. There is a need to develop and design a framework or sensitive data detection model for data leakage prevention.