Anonymization and Identifiability: Enhancing Data Protection Through Differential Privacy and Artificial Intelligence (Global and Comparative Data Law, 8) - Hardcover
Synopsis
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.
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About the Author
Lauritz Gerlach, Hamburg.
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Hardcover. Condition: new. Hardcover. 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9783119142601
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Hardcover. Condition: new. Hardcover. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783119142601
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Anonymization and Identifiability
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Walter De Gruyter Feb 2026, 2026
ISBN 10: 3119142603
ISBN 13: 9783119142601
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Buch. Condition: Neu. Neuware -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.; Daten sind eine zentrale Ressource des 21. Jahrhunderts. Daten dienen individuellen, kollektiven und Gemeinwohlzwecken. Daten und Datenökosysteme prägen die Wettbewerbsfähigkeit von kommerziellen, nicht-kommerziellen und staatlichen Akteuren gleichermaßen. Die Kalibrierung der Nutzung und Nutzungsszenarien von Daten ist eine eminente Frage für (Selbst-)Regulierer - auf dem nationalen, supranationalen und internationalen Level. Globale, vergleichende und interdisziplinäre Perspektiven sind notwendig, um eine adäquate Balance zwischen datenbezogener Kooperation und datenbezogenem Wettbewerb zu erzielen. Diese Perspektiven reichen weit über das Datenschutzrecht hinaus und umfassen unter anderem das Daten(wirtschafts)recht, das Open Data-Recht, das Geheimnisschutzrecht und das Immaterialgüterrecht. Vor diesem Hintergrund widmet sich die Reihe zentralen Fragestellungen des Internationalen und Vergleichenden Datenrechts sowie der Datenpolitik. Die Reihe umfasst Studien und Monographien sowie Tagungs- und Sammelbände. 264 pp. Englisch. Seller Inventory # 9783119142601
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Anonymization and Identifiability
Published by
Walter De Gruyter Feb 2026, 2026
ISBN 10: 3119142603
ISBN 13: 9783119142601
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Buch. Condition: Neu. Neuware -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.; Daten sind eine zentrale Ressource des 21. Jahrhunderts. Daten dienen individuellen, kollektiven und Gemeinwohlzwecken. Daten und Datenökosysteme prägen die Wettbewerbsfähigkeit von kommerziellen, nicht-kommerziellen und staatlichen Akteuren gleichermaßen. Die Kalibrierung der Nutzung und Nutzungsszenarien von Daten ist eine eminente Frage für (Selbst-)Regulierer - auf dem nationalen, supranationalen und internationalen Level. Globale, vergleichende und interdisziplinäre Perspektiven sind notwendig, um eine adäquate Balance zwischen datenbezogener Kooperation und datenbezogenem Wettbewerb zu erzielen. Diese Perspektiven reichen weit über das Datenschutzrecht hinaus und umfassen unter anderem das Daten(wirtschafts)recht, das Open Data-Recht, das Geheimnisschutzrecht und das Immaterialgüterrecht. Vor diesem Hintergrund widmet sich die Reihe zentralen Fragestellungen des Internationalen und Vergleichenden Datenrechts sowie der Datenpolitik. Die Reihe umfasst Studien und Monographien sowie Tagungs- und Sammelbände. 264 pp. Englisch. Seller Inventory # 9783119142601
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