Abstract
In organizations sensitive data transaction is having less security because there may be a misusability of data from one to other from past years. In previous methods they calculated how much data is leaked but didn't find who is leaked. In this paper, we find leakage and leaker. A data distributor has given sensitive data to a set of supposedly trusted agents (third parties). Some of the data has leaked and found in an unauthorized place (e.g., on the web or somebody's laptop). The distributor should assess the likelihood of the leaked data came from one or more agents, as opposed to having independently gathered by others. We propose data allocation strategies (across the agents) that improve the probability of identifying leakages. These methods don't 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.
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