
Anonymization and Identifiability
Enhancing Data Protection Through Differential Privacy and Artificial Intelligence
Lauritz Gerlach(Author)
De Gruyter (Publisher)
1st Edition
Published on 23. January 2026
Book
Hardback
XVI, 264 pages
978-3-11-914260-1 (ISBN)
Description
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.
More details
Series
Language
English
Place of publication
Berlin/Boston
Germany
Target group
Professional and scholarly
US School Grade: College Graduate Student
Illustrations
9 s/w Abbildungen
9 ill.
Dimensions
Height: 231 mm
Width: 159 mm
Thickness: 19 mm
Weight
528 gr
ISBN-13
978-3-11-914260-1 (9783119142601)
Schweitzer Classification
Other editions
Additional editions

Lauritz Gerlach
Anonymization and Identifiability
Enhancing Data Protection Through Differential Privacy and Artificial Intelligence
E-Book
02/2026
1st Edition
De Gruyter
€79.95
Available for download

Lauritz Gerlach
Anonymization and Identifiability
Enhancing Data Protection Through Differential Privacy and Artificial Intelligence
E-Book
02/2026
1st Edition
De Gruyter
€79.95
Available for download
Person
Lauritz Gerlach, Hamburg.