Privacy in Statistical Databases - Lecture Notes in Computer Science
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(FIVE YEARS 25)

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Published By Springer International Publishing

9783030575205, 9783030575212

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An Analysis of Different Notions of Effectiveness in k-Anonymity

Privacy in Statistical Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-030-57521-2_9 ◽

2020 ◽

pp. 121-135

Author(s):

Tanja Šarčević ◽

David Molnar ◽

Rudolf Mayer

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Plausible Deniability

Privacy in Statistical Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-030-57521-2_7 ◽

2020 ◽

pp. 91-105

Author(s):

David Sidi ◽

Jane Bambauer

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Differential Privacy and Its Applicability for Official Statistics in Japan – A Comparative Study Using Small Area Data from the Japanese Population Census

Privacy in Statistical Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-030-57521-2_24 ◽

2020 ◽

pp. 337-352

Author(s):

Shinsuke Ito ◽

Takayuki Miura ◽

Hiroto Akatsuka ◽

Masayuki Terada

Keyword(s):

Comparative Study ◽

Japanese Population ◽

Small Area ◽

Differential Privacy ◽

Population Census ◽

Official Statistics ◽

Area Data

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Integrating Differential Privacy in the Statistical Disclosure Control Tool-Kit for Synthetic Data Production

Privacy in Statistical Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-030-57521-2_19 ◽

2020 ◽

pp. 271-280

Author(s):

Natalie Shlomo

Keyword(s):

Differential Privacy ◽

Synthetic Data ◽

Statistical Disclosure Control ◽

Disclosure Control ◽

Data Production ◽

Statistical Disclosure ◽

Control Tool

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Probabilistic Blocking and Distributed Bayesian Entity Resolution

Privacy in Statistical Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-030-57521-2_16 ◽

2020 ◽

pp. 224-239

Author(s):

Ted Enamorado ◽

Rebecca C. Steorts

Keyword(s):

Entity Resolution

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$$ P_{\alpha ,\beta } $$-Privacy: A Composable Formulation of Privacy Guarantees for Data Publishing Based on Permutation

Privacy in Statistical Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-030-57521-2_1 ◽

2020 ◽

pp. 3-20

Author(s):

Nicolas Ruiz

Keyword(s):

Data Publishing ◽

Alpha Beta

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A Bayesian Nonparametric Approach to Differentially Private Data

Privacy in Statistical Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-030-57521-2_3 ◽

2020 ◽

pp. 32-48

Author(s):

Fadhel Ayed ◽

Marco Battiston ◽

Giuseppe Di Benedetto

Keyword(s):

Bayesian Nonparametric ◽

Nonparametric Approach ◽

Private Data

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$$\epsilon $$-Differential Privacy for Microdata Releases Does Not Guarantee Confidentiality (Let Alone Utility)

Privacy in Statistical Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-030-57521-2_2 ◽

2020 ◽

pp. 21-31

Author(s):

Krishnamurty Muralidhar ◽

Josep Domingo-Ferrer ◽

Sergio Martínez

Keyword(s):

Differential Privacy

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Calculation of Risk Probabilities for the Cell Key Method

Privacy in Statistical Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-030-57521-2_11 ◽

2020 ◽

pp. 151-165

Author(s):

Tobias Enderle ◽

Sarah Giessing ◽

Reinhard Tent

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Multivariate Top-Coding for Statistical Disclosure Limitation

Privacy in Statistical Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-030-57521-2_10 ◽

2020 ◽

pp. 136-148

Author(s):

Anna Oganian ◽

Ionut Iacob ◽

Goran Lesaja

Keyword(s):

Disclosure Limitation ◽

Statistical Disclosure Limitation ◽

Statistical Disclosure

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Privacy in Statistical Databases - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

An Analysis of Different Notions of Effectiveness in k-Anonymity

Plausible Deniability

Differential Privacy and Its Applicability for Official Statistics in Japan – A Comparative Study Using Small Area Data from the Japanese Population Census

Integrating Differential Privacy in the Statistical Disclosure Control Tool-Kit for Synthetic Data Production

Probabilistic Blocking and Distributed Bayesian Entity Resolution

$$ P_{\alpha ,\beta } $$-Privacy: A Composable Formulation of Privacy Guarantees for Data Publishing Based on Permutation

A Bayesian Nonparametric Approach to Differentially Private Data

$$\epsilon $$-Differential Privacy for Microdata Releases Does Not Guarantee Confidentiality (Let Alone Utility)

Calculation of Risk Probabilities for the Cell Key Method

Multivariate Top-Coding for Statistical Disclosure Limitation

Privacy in Statistical Databases - Lecture Notes in Computer Science
Latest Publications