  Data Loss/Leakage Prevention (DLP) continues to be the main issue for many
large organizations. There are multiple numbers of emerging security attach
scenarios and a limitless number of overcoming solutions. Today's enterprises'
major concern is to protect confidential information because a leakage that
compromises confidential data means that sensitive information is in
competitors' hands. Different data types need to be protected. However, our
research is focused only on data in motion (DIM) i-e data transferred through
the network. The research and scenarios in this paper demonstrate a recent
survey on information and data leakage incidents, which reveals its importance
and also proposed a model solution that will offer the combination of previous
methodologies with a new way of pattern matching by advanced content checker
based on the use of machine learning to protect data within an organization and
then take actions accordingly. This paper also proposed a DLP deployment design
on the gateway level that shows how data is moving through intermediate
channels before reaching the final destination using the squid proxy server and
ICAP server.
