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  • Produktbild: Privacy in Statistical Databases
Band 13463

Privacy in Statistical Databases International Conference, PSD 2022, Paris, France, September 21–23, 2022, Proceedings

Aus der Reihe Lecture Notes in Computer Science

49,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

05.08.2022

Herausgeber

Josep Domingo-Ferrer + weitere

Verlag

Springer

Seitenzahl

376

Maße (L/B/H)

23,5/15,5/2,1 cm

Gewicht

587 g

Auflage

1st edition 2022

Sprache

Englisch

ISBN

978-3-031-13944-4

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

05.08.2022

Herausgeber

Verlag

Springer

Seitenzahl

376

Maße (L/B/H)

23,5/15,5/2,1 cm

Gewicht

587 g

Auflage

1st edition 2022

Sprache

Englisch

ISBN

978-3-031-13944-4

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Privacy in Statistical Databases
  • Produktbild: Privacy in Statistical Databases
  • ¿Privacy models.- An optimization-based decomposition heuristic for the microaggregation problem.- Privacy Analysis with a Distributed Transition System and a data-wise metric.- Multivariate Mean Comparison under Differential Privacy.- Asking The Proper Question: Adjusting Queries To Statistical Procedures Under

    Differential Privacy.- Towards integrally private clustering: overlapping clusters for high privacy guarantees.-  Tabular data.- Perspectives for Tabular Data Protection - How About Synthetic Data?.- On Privacy of Multidimensional Data Against Aggregate Knowledge Attacks.- Synthetic Decimal Numbers as a Flexible Tool for Suppression of Post-published Tabular Data.-  Disclosure risk assessment and record linkage.- The risk of disclosure when reporting commonly used univariate statistics.-  Privacy-Preserving protocols.- Tit-for-Tat Disclosure of a Binding Sequence of User Analysesin Safe Data Access Centers.- Secure and non-interactive k-NN classifier using symmetric fully homomorphic encryption.-  Unstructured and mobility data.- Automatic evaluation of disclosure risks of text anonymization methods.- Generation of Synthetic Trajectory Microdata from Language Models.-  Synthetic data.- Synthetic Individual Income Tax Data: Methodology, Utility, and Privacy Implications.- On integrating the number of synthetic data sets m into the a priori synthesis approach .- Challenges in Measuring Utility for Fully Synthetic Data.- Comparing the Utility and Disclosure Risk of Synthetic Data with Samples of Microdata.- Utility and Disclosure Risk for Differentially Private Synthetic Categorical Data.-  Machine learning and privacy.- Membership Inference Attack Against Principal Component Analysis.- When Machine Learning Models Leak: An Exploration of Synthetic Training Data.-  Case studies.- A Note on the Misinterpretation of the US Census Re-identification Attack.- A Re-examination of the Census Bureau Reconstruction and Reidentification Attack.- Quality Assessment of the 2014 to 2019 National Survey on Drug Use and Health (NSDUH) Public Use Files.- Privacy in Practice: Latest Achievements of the EUSTAT SDC group.- How Adversarial Assumptions Influence Re- identification Risk Measures: A COVID-19 Case Study.