Category: Publication

The Pitfalls of Hashing for Privacy

Boosted by recent legislations, data anonymization is fast becoming a norm. However, as of yet no generic solution has been found to safely release data. As a consequence, data custodians often resort to ad-hoc means to anonymize datasets. Both past and current practices indicate that hashing is often believed to be an effective way to …

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Differentially Private Mixture of Generative Neural Networks

Generative models are used in a wide range of applications building on large amounts of contextually rich information. Due to possible privacy violations of the individuals whose data is used to train these models, however, publishing or sharing generative models is not always viable. In [4], we develop a novel technique for privately releasing generative …

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A refinement approach for the reuse of privacy risk analysis results

With the adoption of the EU General Data Protection Regulation (GDPR), conducting a data protection impact assessment will become mandatory for certain categories of personal data processing. A large body of literature has been devoted to data protection impact assessment and privacy impact assessment. However, most of these papers focus on legal and organizational aspects …

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