Privacy in Statistical Databases (eBook, PDF)
UNESCO Chair in Data Privacy, International Conference, PSD 2014, Ibiza, Spain, September 17-19, 2014. Proceedings
Redaktion: Domingo-Ferrer, Josep
40,95 €
40,95 €
inkl. MwSt.
Sofort per Download lieferbar
20 °P sammeln
40,95 €
Als Download kaufen
40,95 €
inkl. MwSt.
Sofort per Download lieferbar
20 °P sammeln
Jetzt verschenken
Alle Infos zum eBook verschenken
40,95 €
inkl. MwSt.
Sofort per Download lieferbar
Alle Infos zum eBook verschenken
20 °P sammeln
Privacy in Statistical Databases (eBook, PDF)
UNESCO Chair in Data Privacy, International Conference, PSD 2014, Ibiza, Spain, September 17-19, 2014. Proceedings
Redaktion: Domingo-Ferrer, Josep
- Format: PDF
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung
Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei
bücher.de, um das eBook-Abo tolino select nutzen zu können.
Hier können Sie sich einloggen
Hier können Sie sich einloggen
Sie sind bereits eingeloggt. Klicken Sie auf 2. tolino select Abo, um fortzufahren.
Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei bücher.de, um das eBook-Abo tolino select nutzen zu können.
This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2014, held in Ibiza, Spain in September 2014 under the sponsorship of the UNESCO chair in Data Privacy. The 27 revised full papers presented were carefully reviewed and selected from 41 submissions. The scope of the conference is on following topics: tabular data protection, microdata masking, protection using privacy models, synthetic data, record linkage, remote access, privacy-preserving protocols, and case studies.
- Geräte: PC
- ohne Kopierschutz
- eBook Hilfe
- Größe: 6.74MB
Andere Kunden interessierten sich auch für
- Privacy in Statistical Databases (eBook, PDF)40,95 €
- Generative AI in e-Business (eBook, PDF)40,95 €
- E-Government, E-Services and Global Processes (eBook, PDF)40,95 €
- Digital Transformation in the Viral Age (eBook, PDF)73,95 €
- Advances in Multimedia Information Processing - PCM 2017 (eBook, PDF)81,95 €
- South African Computer Science and Information Systems Research Trends (eBook, PDF)97,95 €
- Advances in Multimedia Information Processing - PCM 2017 (eBook, PDF)113,95 €
-
-
-
This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2014, held in Ibiza, Spain in September 2014 under the sponsorship of the UNESCO chair in Data Privacy. The 27 revised full papers presented were carefully reviewed and selected from 41 submissions. The scope of the conference is on following topics: tabular data protection, microdata masking, protection using privacy models, synthetic data, record linkage, remote access, privacy-preserving protocols, and case studies.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Springer International Publishing
- Seitenzahl: 367
- Erscheinungstermin: 10. September 2014
- Englisch
- ISBN-13: 9783319112572
- Artikelnr.: 44128427
- Verlag: Springer International Publishing
- Seitenzahl: 367
- Erscheinungstermin: 10. September 2014
- Englisch
- ISBN-13: 9783319112572
- Artikelnr.: 44128427
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Tabular Data Protection.- Enabling Statistical Analysis of Suppressed Tabular Data.- Assessing the Information Loss of Controlled Adjustment Methods in Two-Way Tables.- Further Developments with Perturbation Techniques to Protect Tabular Data.- Comparison of Different Sensitivity Rules for Tabular Data and Presenting a New Rule - The Interval Rule.- Pre-tabular Perturbation with Controlled Tabular Adjustment: Some Considerations.- Measuring Disclosure Risk with Entropy in Population Based Frequency Tables.- A CTA Model Based on the Huber Function.- Microdata Masking Density Approximant Based on Noise Multiplied Data.- Reverse Mapping to Preserve the Marginal Distributions of Attributes in Masked Microdata .- JPEG-Based Microdata Protection.- Protection Using Privacy Models.- Improving the Utility of Differential Privacy via Univariate Microaggregation.- Differentially Private Exponential Random Graphs.- km-Anonymity for Continuous Data Using Dynamic Hierarchies.- Differentially-Private Logistic Regression for Detecting Multiple-SNP Association in GWAS Databases.- Synthetic Data.- Disclosure Risk Evaluation for Fully Synthetic Categorical Data.- v-Dispersed Synthetic Data Based on a Mixture Model with Constraints.- Nonparametric Generation of Synthetic Data for Small Geographic Areas.- Using Partially Synthetic Data to Replace Suppression in the Business Dynamics Statistics: Early Results.- Synthetic Longitudinal Business Databases for International Comparisons .- Record Linkage.- A Comparison of Blocking Methods for Record Linkage.- Probabilistic Record Linkage for Disclosure Risk Assessment.- Hierarchical Linkage Clustering with Distributions of Distances for Large-Scale Record Linkage.- Remote Access.- Comparison of Two Remote Access Systems Recently Developed and Implemented in Australia.- Privacy-Preserving Protocols.- Towards Secure and Practical Location Privacy through Private Equality Testing.- Case Studies.- Controlled Shuffling, StatisticalConfidentiality and Microdata Utility: A Successful Experiment with a 10% Household Sample of the 2011 Population Census of Ireland for the IPUMS-International Database.- Balancing Confidentiality and Usability: Protecting Sensitive Data in the Case of Inward Foreign AffiliaTes Statistics (FATS).- Applicability of Confidentiality Methods to Personal and Business Data.
Tabular Data Protection.- Enabling Statistical Analysis of Suppressed Tabular Data.- Assessing the Information Loss of Controlled Adjustment Methods in Two-Way Tables.- Further Developments with Perturbation Techniques to Protect Tabular Data.- Comparison of Different Sensitivity Rules for Tabular Data and Presenting a New Rule - The Interval Rule.- Pre-tabular Perturbation with Controlled Tabular Adjustment: Some Considerations.- Measuring Disclosure Risk with Entropy in Population Based Frequency Tables.- A CTA Model Based on the Huber Function.- Microdata Masking Density Approximant Based on Noise Multiplied Data.- Reverse Mapping to Preserve the Marginal Distributions of Attributes in Masked Microdata .- JPEG-Based Microdata Protection.- Protection Using Privacy Models.- Improving the Utility of Differential Privacy via Univariate Microaggregation.- Differentially Private Exponential Random Graphs.- km-Anonymity for Continuous Data Using Dynamic Hierarchies.- Differentially-Private Logistic Regression for Detecting Multiple-SNP Association in GWAS Databases.- Synthetic Data.- Disclosure Risk Evaluation for Fully Synthetic Categorical Data.- v-Dispersed Synthetic Data Based on a Mixture Model with Constraints.- Nonparametric Generation of Synthetic Data for Small Geographic Areas.- Using Partially Synthetic Data to Replace Suppression in the Business Dynamics Statistics: Early Results.- Synthetic Longitudinal Business Databases for International Comparisons .- Record Linkage.- A Comparison of Blocking Methods for Record Linkage.- Probabilistic Record Linkage for Disclosure Risk Assessment.- Hierarchical Linkage Clustering with Distributions of Distances for Large-Scale Record Linkage.- Remote Access.- Comparison of Two Remote Access Systems Recently Developed and Implemented in Australia.- Privacy-Preserving Protocols.- Towards Secure and Practical Location Privacy through Private Equality Testing.- Case Studies.- Controlled Shuffling, StatisticalConfidentiality and Microdata Utility: A Successful Experiment with a 10% Household Sample of the 2011 Population Census of Ireland for the IPUMS-International Database.- Balancing Confidentiality and Usability: Protecting Sensitive Data in the Case of Inward Foreign AffiliaTes Statistics (FATS).- Applicability of Confidentiality Methods to Personal and Business Data.