Anonymization and Identifiability: Enhancing Data Protection Through Differential Privacy and Artificial Intelligence
Author:   Lauritz Gerlach
Publisher:   De Gruyter
ISBN:  

9783119142601


Pages:   280
Publication Date:   29 December 2025
Format:   Hardback
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

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Anonymization and Identifiability: Enhancing Data Protection Through Differential Privacy and Artificial Intelligence


Overview

The author explores the nature of data anonymization under the GDPR, with a particular focus on means of differential privacy. First, he examines the requirement of „identified or identifiable“ in Art. 4 GDPR. Building on this foundation, he describes and evaluates different methods for the anonymization of structured and unstructured data, especially text data. The author describes the role of machine learning and artificial intelligence with regard to anonymizing unstructured data and elaborates on the data protection implications of training and using AI/ML models (including federated learning setups) for this purpose.

Full Product Details

Author:   Lauritz Gerlach
Publisher:   De Gruyter
Imprint:   De Gruyter
Weight:   0.500kg
ISBN:  

9783119142601


ISBN 10:   3119142603
Pages:   280
Publication Date:   29 December 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Forthcoming
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

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Author Information

Lauritz Gerlach, Hamburg. 

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Latest Reading Guide

NOV RG 20252

 

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