Privacy in Statistical Databases [recurso electrónico] : UNESCO Chair in Data Privacy, International Conference, PSD 2010, Corfu, Greece, September 22-24, 2010. Proceedings / edited by Josep Domingo-Ferrer, Emmanouil Magkos.
Tipo de material:
TextoSeries Lecture Notes in Computer Science ; 6344Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Descripción: XI, 297p. 47 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642158384Tema(s): Computer science | Computer Communication Networks | Data protection | Data structures (Computer science) | Data encryption (Computer science) | Database management | Computer Science | Database Management | Computer Communication Networks | Systems and Data Security | Data Encryption | Data Structures | Data Structures, Cryptology and Information TheoryFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 005.74 Clasificación LoC:QA76.9.D3Recursos en línea: Libro electrónico
En: Springer eBooksResumen: 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).
| Tipo de ítem | Biblioteca actual | Colección | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras |
|---|---|---|---|---|---|---|---|
| Libro Electrónico | Biblioteca Electrónica | Colección de Libros Electrónicos | QA76.9 .D3 (Browse shelf(Abre debajo)) | 1 | No para préstamo | 375148-2001 |
Navegando Biblioteca Electrónica Estantes, Código de colección: Colección de Libros Electrónicos Cerrar el navegador de estanterías (Oculta el navegador de estanterías)
| QA76.9 .D3 Data Management in Grid and Peer-to-Peer Systems | QA76.9 .D3 Advances in Databases and Information Systems | QA76.9 .D3 Database and XML Technologies | QA76.9 .D3 Privacy in Statistical Databases | QA76.9 .D3 Objects and Databases | QA76.9 .D3 Transactions on Large-Scale Data- and Knowledge-Centered Systems II | QA76.9 .D3 Schema Matching and Mapping |
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).
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