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Abstract
— A data distributor has given sensitive data to a set of supposedly trusted agents (third parties). Some amount of data is leaked and found in an unauthorized machines (e.g., on the internet or computer). The distributor has to find out from whom that data get leaked. We propose data allocation strategies (across the agents) that increase the chances of detecting leakages. These techniques do not need to modify data of the released data (e.g., watermarks). In some cases we can also embed real but fake data records to further increase our chances of detecting leakage and identifying the guilty agent. Our goal is to detect when the distributors sensitive data has been leaked by agents, and detect the agent that leaked the data. Perturbation is a very useful method where the data is modified and made less sensitive before being handed to agents. we develop secure techniques for detecting leakage of a set of objects or records.
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Index Terms – Data leakage, Detection Guilty Agent, Distributor .
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References
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