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Privacy in Statistical Databases International Conference, PSD 2024, Antibes Juan-les-Pins, France, September 25-27, 2024, Proceedings
Title
Privacy in Statistical Databases [electronic resource] : International Conference, PSD 2024, Antibes Juan-les-Pins, France, September 25-27, 2024, Proceedings / edited by Josep Domingo-Ferrer, Melek Önen.
ISBN
9783031696510
Edition
1st ed. 2024.
Publication
Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Physical Description
1 online resource (XI, 438 p.) 118 illus., 77 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2024, held in Antibes Juan-les-Pins, France, during September 25-27, 2024. The 28 papers presented in this volume were carefully reviewed and selected from 46 submissions. They were organized in topical sections as follows: Privacy models and concepts; Microdata protection; Statistical table protection; Synthetic data generation methods; Synthetic data generation software; Disclosure risk assessment; Spatial and georeferenced data; Machine learning and privacy; and Case studies. .
Variant and related titles
Springer ENIN.
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Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
October 14, 2024
Series
Lecture Notes in Computer Science, 14915
Contents
Privacy models and concepts
Microdata protection
Statistical table protection
Synthetic data generation methods
Synthetic data generation software
Disclosure risk assessment
Spatial and georeferenced data
Machine learning and privacy
Case studies.
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