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Privacy in statistical databases = International Conference, PSD 2024, Antibes Juan-Les-Pins, France, September 25-27, 2024 : proceedings /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Privacy in statistical databases/ edited by Josep Domingo-Ferrer, Melek Önen.
其他題名:	International Conference, PSD 2024, Antibes Juan-Les-Pins, France, September 25-27, 2024 : proceedings /
其他作者:	Domingo-Ferrer, Josep.
團體作者:	Workshop on the Preservation of Stability under Discretization
出版者:	Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:	xi, 438 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Database security - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-031-69651-0
ISBN:	9783031696510

Privacy in statistical databases = International Conference, PSD 2024, Antibes Juan-Les-Pins, France, September 25-27, 2024 : proceedings /
Privacy in statistical databasesInternational Conference, PSD 2024, Antibes Juan-Les-Pins, France, September 25-27, 2024 : proceedings /[electronic resource] :edited by Josep Domingo-Ferrer, Melek Önen. - Cham :Springer Nature Switzerland :2024. - xi, 438 p. :ill., digital ;24 cm. - Lecture notes in computer science,149150302-9743 ;. - Lecture notes in computer science,7131. .

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.

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.

ISBN: 9783031696510

Standard No.: 10.1007/978-3-031-69651-0doiSubjects--Topical Terms:

675402
Database security
--Congresses.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 005.8

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