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22 lines
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22 lines
1 KiB
Markdown
# anonymization module
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This module contains methods for anonymizing ML model training data, so that when
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a model is retrained on the anonymized data, the model itself will also be considered
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anonymous. This may help exempt the model from different obligations and restrictions
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set out in data protection regulations such as GDPR, CCPA, etc.
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The module contains methods that enable anonymizing training datasets in a manner that
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is tailored to and guided by an existing, trained ML model. It uses the existing model's
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predictions on the training data to train a second, anonymizer model, that eventually determines
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the generalizations that will be applied to the training data. For more information about the
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method see: https://arxiv.org/abs/2007.13086
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Once the anonymized training data is returned, it can be used to retrain the model.
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The following figure depicts the overall process:
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<p align="center">
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<img src="../../docs/images/AI_Privacy_project2.jpg?raw=true" width="667" title="anonymization process">
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</p>
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<br />
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