Probability of Data Leckage in Cloud Computing

Abstract

A distributor data has given touchy information to a fixed of hypothetically relied on agents (0.33 events). Any of the records are disclosed in an unconstitutional location (e.g. on the net or somebody's computer) and decided. The dispenser will assess the probability that the revealed data came from one or more vendors, as opposite to being collected separately by various means. We suggest records distribution plans (throughout the sellers) that improve the chance of figuring out leakages. These techniques do now not rely on alterations of the launched information (e.g., watermarks). In some cases, we also can inject “sensible however faux” information to in addition enhance our probabilities of detecting leakage and figuring out the guilty celebration Many small business authorities have data leak issues via internet or other means. We would like to propose a alternative methodology to implement in real world and it is different from traditional methods. But this also will not work if the guilt agent knows the fake objects. So the other method for getting the guilt agents is to be determined. Many methods have been in existence but every method is being override by other means using complex methodologies and by various combinations of the algorithms. These complex methods would secure much better than older ones. We are finding the agents by taking the parameters like how much time he is spending in the data, how many times he opened that file etc... We can find the probability if the probability is more than the threshold value then we can conclude that the agent had compromised. In this model we use the previous methods knowledge to predict the agents or to overcome in the solution.