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EU-GDPR: State-of-the-Art Anonymisation and Pseudonymisation of Data



EU-GDPR: State-of-the-Art Anonymisation and Pseudonymisation of Data


Question: How to select adequate methods for anonymising and pseudonymising data?

The guide for companies published by Bitkom e.V. provides a technical overview of methods for the anonymisation and pseudonymization of data. Chapter 9 describes the "Semantic Anonymisation of Sensitive Data with Inference-based AI and Active Ontologies".

In contrast to previous methods (e.g., differential privacy), this new AI-based approach largely preserves the information value of the raw data and allows for a privacy-compliant analysis of personal data, which ensures that the original persons can no longer be identified and also prevents personal traceability via quasi-identifiers (two-way security). Large amounts of sensitive data can be used with this method in a way that complies with data protection regulations, but at the same time preserves the potential for analysis.


Use cases:

1. The data analysis for product development or optimisation of marketing campaigns and an improved customer approach. 2. The generation of test data from production data for realistic tests of interfaces and IT processes.

bitkom Publication 2020_Semantic Anonymi
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