LEADER 03991nam 2200637 a 450 001 9910484999003321 005 20200520144314.0 010 $a3-642-15838-2 024 7 $a10.1007/978-3-642-15838-4 035 $a(CKB)2670000000045110 035 $a(SSID)ssj0000446711 035 $a(PQKBManifestationID)11269487 035 $a(PQKBTitleCode)TC0000446711 035 $a(PQKBWorkID)10504598 035 $a(PQKB)11673199 035 $a(DE-He213)978-3-642-15838-4 035 $a(MiAaPQ)EBC3065886 035 $z(PPN)147972329 035 $a(PPN)149031777 035 $a(EXLCZ)992670000000045110 100 $a20100805d2010 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aPrivacy in statistical databases $eUNESCO Chair in Data Privacy, International Conference, PSD 2010, Corfu, Greece, September 22-24, 2010 : proceedings /$fJosep Domingo-Ferrer, Emmanouil Magkos (eds.) 205 $a1st ed. 2010. 210 $aNew York $cSpringer$d2010 215 $a1 online resource (XI, 297 p. 47 illus.) 225 1 $aLecture notes in computer science,$x0302-9743 ;$v6344 225 1 $aLNCS sublibrary. SL 3, Information systems and applications, incl. Internet/Web, and HCI 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-642-15837-4 320 $aIncludes bibliographical references and index. 330 $aPrivacy in statistical databases is a discipline whose purpose is to provide so- tionstothetensionbetweenthesocial,political,economicandcorporatedemand for accurate information, and the legal and ethical obligation to protect the p- vacy of the various parties involved. Those parties are the respondents (the individuals and enterprises to which the database records refer), the data o- ers (those organizations spending money in data collection) and the users (the ones querying the database or the search engine, who would like their queries to stay con?dential). Beyond law and ethics, there are also practical reasons for data-collecting agencies and corporations to invest in respondent privacy: if individual respondents feel their privacy guaranteed, they are likely to provide moreaccurateresponses. Data ownerprivacyis primarilymotivatedbypractical considerations: if an enterprise collects data at its own expense, it may wish to minimize leakage of those data to other enterprises (even to those with whom joint data exploitation is planned). Finally, user privacy results in increaseduser satisfaction, even if it may curtail the ability of the database owner to pro?le users. Thereareatleasttwotraditionsinstatisticaldatabaseprivacy,bothofwhich started in the 1970s: the ?rst one stems from o?cial statistics, where the dis- pline is also known as statistical disclosure control (SDC), and the second one originates from computer science and database technology. In o?cial statistics, the basic concern is respondent privacy. In computer science, the initial mo- vation was also respondent privacy but, from 2000 onwards, growing attention has been devoted to owner privacy (privacy-preserving data mining) and user privacy (private informationretrieval). 410 0$aLecture notes in computer science ;$v6344. 410 0$aLNCS sublibrary.$nSL 3,$pInformation systems and applications, incl. Internet/Web, and HCI. 606 $aComputer security$vCongresses 606 $aDatabases$xStatistics$vCongresses 606 $aData protection$vCongresses 615 0$aComputer security 615 0$aDatabases$xStatistics 615 0$aData protection 676 $a005.8 701 $aDomingo-Ferrer$b Josep$01751715 701 $aMagkos$b Emmanouil$01752949 712 02$aUNESCO Chair in Data Privacy. 712 12$aPSD 2010 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484999003321 996 $aPrivacy in statistical databases$94188459 997 $aUNINA