Abstract
Detailed patient data are crucial for medical research. Yet, these healthcare data can only be released for secondary use if they have undergone anonymization. We present and describe µ-ANT, a practical and easily configurable anonymization tool for (healthcare) data. It implements several state-of-the-art methods to offer robust privacy guarantees and preserve the utility of the anonymized data as much as possible. µ-ANT also supports the heterogenous attribute types commonly found in electronic healthcare records and targets both practitioners and software developers interested in data anonymization. (source code, documentation, executable, sample datasets and use case examples) https://github.com/CrisesUrv/microaggregation-based_anonymization_tool.
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