Optimizing Data Misuse Detection by Identifying Guilty Agent without Causing Disturbance and Inconvenience to Trusted Agent

Now a day's in fact engaged data rich environment, prevention of data misuse is a challengeable field for data holders. A Data misuse is the way toward preventing delicate data by unauthorized people. There are distinctive ways for identifying the data misuse from untrusted agents. There are some diverse systems and techniques received for recognizing data misuse. To defeat the impediments of conventional frameworks, data portion systems are utilized to enhance the likelihood of recognizing guilty outsiders, without changing the first data. The proposition is to disperse the data with insight to agents in view of express data demand and test data demand keeping in mind the end goal to enhance the shot of identifying the guilty agents. On the off chance that any operator is leaks a part of conveyed data that agent is called guilty agent. The heuristic calculations are utilized to execute the blame on agent detection by including fake objects that enhance the distributor possibility of distinguishing guilty agents. Exploratory assessments demonstrate that specified proposed methods are effective and enhance the likelihood for finding the guilty agents in expansive observation database s gathered by frameworks.