In the business, sometimes sensitive data must be handed over to trusted third parties. So some companies distribute their data to trusted third parties. These companies (data distributer) found their some of the data in unauthorized place (e.g., on the web or somebody's laptop). The distributor understands that the leaked data came from one or more agents. Our goal is to detect which agent leaks that data and provide the security to that data.
When the distributor's sensitive data have been leaked by agents, and to identify the agent that leaked the data. We propose data allocation strategies (across the agents) that improve the probability of identifying leakages. These methods do not rely on alterations of the released data (e.g., watermarks). In some cases we can also inject “realistic but fake” data records to further improve our chances of detecting leakage and identifying the guilty party. The Main Aim of the system can be given as follows: -
Identify data leakages from distributed data using some data allocation strategies and find out the fake agent who leak that data. Improve probability of finding out fake agent and provide the security to that data.
DLD(Data Leakage Detection)
