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Data leakage is at the heart most of the privacy breaches worldwide. In this paper we present a white-box approach to detect potential data leakage by spotting anomalies in database transactions. We refer to our solution as white-box because it builds self explanatory profiles that are easy to understand and update, as opposite to black-box systems which create profiles hard to interpret and maintain (e.g., neural networks). In this paper we introduce our approach and we demonstrate that it is a major leap forward w.r.t. previous work on the topic in several aspects: (i) it significantly decreases the number of false positives, which is orders of magnitude lower than in state-of-the-art comparable approaches (we demonstrate this using an experimental dataset consisting of millions of real enterprise transactions); (ii) it creates profiles that are easy to understand and update, and therefore it provides an explanation of the …