A Model for Improving Guilt Probabilities to Identify Data Leackages

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Provided by: IJESAT (International Journal of Engineering Science & Advanced Technology)
Topic: Big Data
Format: PDF
Sometimes sensitive data may be distributes by a data distributor to a set of trusted agents (third parties), but some of the distributed data the users may find in an unauthorized website or systems. So the distributor must assess the probability of data leakage from its trusted agents. So in this paper the authors propose a model for assessing the guilt probability of agents, in a way that improves the chances of identifying a data leakage. They also propose algorithms for distributing objects to agents.
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