• Sam Soloman

Data leakage has become one of the growing internal risk in InfoSec and among many enterprises and personnel. Multiple ways have been created and deployed to inscribe the issues of data leakage prevention (DLP). Nevertheless, huge amounts of unorganized data must be analyzed and secured in our ever growing and evolving data. Because the size of data is growing exponentially and the structure of data have become more complicated and denser to manage, which has become a new threat for DLP and brings the question how these data can be processed and used efficiently. As a solution we introduce a method called Flexible weighted Graph model (FGM) which helps by aligning it to the elements of the weighted graphs. By adapting this approach, we can solve the problem in three steps. First, the weighted graphs can evaluate the sensitivity of the approved data based on the information passed. The second step is, the improved label propagation which can increase the scalability of the raw data. The third step is a low-complexity measuring algorithm is designed to analyze the furthest sensitiveness.

"A Detection Mechanism for Data Leakage", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.655-660, April-2019, Available :http://www.jetir.org/papers/JETIR1904D88.pdf

"A Detection Mechanism for Data Leakage", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp655-660, April-2019, Available at : http://www.jetir.org/papers/JETIR1904D88.pdf