Dynamically Configurable Document Model to Prevent Data Leakage

Abstract

Recent advancement in the technology has given insights to data security research. As the data storage grows, the threats also increase. Data leakage is one of the most prime importance to be monitored by the organizations because, the enterprises and their businessess and business decision more rely on the data generating in the organization day by day. Since, organizations have to give up some credentials to the employee or vendors to access their sensitive data based on their roles. Organizations are facing difficulty in monitoring the internal employee threats. Several researchers have come up with variety of approaches to prevent data leakage. There are several Data Leakage Detection and Data Leakage Prevention techniques for securing and protecting data. A recently proposed technique addresses the issue of data leakage in transferred data by sampling and matching techniques. This includes different types of algorithms to detect and prevent data leak are either partially or fully. This is more effective than the currently available method in terms of the level of information loss. The proposed approach performs prediction and probability finding in order to identify and protect data from leakers. The experimental result shows the effective results on the distributed data in email security. Today s world needs most of the things would be automated, the machine would be able to do itself everything by its own, from initiation of job to till the decision-making capabilities. Similarly, the Security of the data needs the automated, self-decision and self-protective proactive mechanisms. Since, the existing tools and mechanisms are semi-automated still it needs the human intervention to update and configure the security layers and features. This work gives the mechanism of preventing data leakage by automated machine host based runtime system. Already the few of the data leakage Prevention techniques in place to monitor the behavior of their employees, and users, those who have the credentials to enter into the o