Information Systems and Applications, incl. Internet/Web, and HCI

Privacy in Statistical Databases

UNESCO Chair in Data Privacy, International Conference, PSD 2010, Corfu, Greece, September 22-24, 2010, Proceedings

Editors: Domingo-Ferrer, Josep, Magkos, Emmanouil (Eds.)

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About this book

Privacy in statistical databases is a discipline whose purpose is to provide so- tionstothetensionbetweenthesocial,political,economicandcorporatedemand for accurate information, and the legal and ethical obligation to protect the p- vacy of the various parties involved. Those parties are the respondents (the individuals and enterprises to which the database records refer), the data o- ers (those organizations spending money in data collection) and the users (the ones querying the database or the search engine, who would like their queries to stay con?dential). Beyond law and ethics, there are also practical reasons for data-collecting agencies and corporations to invest in respondent privacy: if individual respondents feel their privacy guaranteed, they are likely to provide moreaccurateresponses. Data ownerprivacyis primarilymotivatedbypractical considerations: if an enterprise collects data at its own expense, it may wish to minimize leakage of those data to other enterprises (even to those with whom joint data exploitation is planned). Finally, user privacy results in increaseduser satisfaction, even if it may curtail the ability of the database owner to pro?le users. Thereareatleasttwotraditionsinstatisticaldatabaseprivacy,bothofwhich started in the 1970s: the ?rst one stems from o?cial statistics, where the dis- pline is also known as statistical disclosure control (SDC), and the second one originates from computer science and database technology. In o?cial statistics, the basic concern is respondent privacy. In computer science, the initial mo- vation was also respondent privacy but, from 2000 onwards, growing attention has been devoted to owner privacy (privacy-preserving data mining) and user privacy (private informationretrieval).

Table of contents (25 chapters)

  • Privacy Disclosure Analysis and Control for 2D Contingency Tables Containing Inaccurate Data

    Liang, Bing (et al.)

    Pages 1-16

  • A Tool for Analyzing and Fixing Infeasible RCTA Instances

    Castro, Jordi (et al.)

    Pages 17-28

  • Branch-and-Cut versus Cut-and-Branch Algorithms for Cell Suppression

    Salazar-González, Juan-José

    Pages 29-40

  • Data Swapping for Protecting Census Tables

    Shlomo, Natalie (et al.)

    Pages 41-51

  • Eliminating Small Cells from Census Counts Tables: Some Considerations on Transition Probabilities

    Giessing, Sarah (et al.)

    Pages 52-65

Buy this book

eBook $79.99
price for USA (gross)
  • ISBN 978-3-642-15838-4
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $109.00
price for USA
  • ISBN 978-3-642-15837-7
  • Free shipping for individuals worldwide
  • Online orders shipping within 2-3 days.
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Bibliographic Information

Bibliographic Information
Book Title
Privacy in Statistical Databases
Book Subtitle
UNESCO Chair in Data Privacy, International Conference, PSD 2010, Corfu, Greece, September 22-24, 2010, Proceedings
Editors
  • Josep Domingo-Ferrer
  • Emmanouil Magkos
Series Title
Information Systems and Applications, incl. Internet/Web, and HCI
Series Volume
6344
Copyright
2010
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-15838-4
DOI
10.1007/978-3-642-15838-4
Softcover ISBN
978-3-642-15837-7
Edition Number
1
Number of Pages
XI, 297
Number of Illustrations and Tables
47 b/w illustrations
Topics