Hiding the presence of individuals from shared databases

Advances in information technology, and its use in research, are increasing both the need for anonymized data and the risks of poor anonymization. We present a metric, δ-presence, that clearly links the quality of anonymization to the risk posed by inadequate anonymization. We show that existing anonymization techniques are inappropriate for situations where δ-presence is a good metric (specifically, where knowing an individual is in the database poses a privacy risk), and present algorithms for effectively anonymizing to meet δ-presence. The algorithms are evaluated in the context of a real-world scenario, demonstrating practical applicability of the approach.