LEADER 02149nam  2200517   450 
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010   $a3-030-57521-7
024 7 $a10.1007/978-3-030-57521-2
035   $a(CKB)4100000011457864
035   $a(DE-He213)978-3-030-57521-2
035   $a(MiAaPQ)EBC6350787
035   $a(PPN)250220504
035   $a(EXLCZ)994100000011457864
100   $a20210211d2020      uy             0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aPrivacy in statistical databases $eUNESCO Chair in Data Privacy, International Conference, PSD 2020, Tarragona, Spain, September 23-25, 2020 : proceedings /$fJosep Domingo-Ferrer, Krishnamurty Muralidhar (editors)
205   $a1st ed. 2020.
210  1$aCham, Switzerland :$cSpringer,$d[2020]
210  4$dİ2020
215   $a1 online resource (XI, 370 p. 25 illus.) 
225 1 $aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v12276
311   $a3-030-57520-9 
327   $aPrivacy models -- Microdata protection -- Protection of statistical tables -- Protection of interactive and mobility databases -- Record linkage and alternative methods -- Synthetic data -- Data quality -- Case studies.
330   $aThe Chapter ?Explaining recurrent machine learning models: integral privacy revisited? is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
410  0$aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v12276
606   $aDatabase security$vCongresses
606   $aData protection$vCongresses
606   $aStatistics$xDatabases$vCongresses
615  0$aDatabase security
615  0$aData protection
615  0$aStatistics$xDatabases
676   $a005.8
702   $aDomingo-Ferrer$b Josep
702   $aMuralidhar$b Krishnamurty
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a996418295203316
996   $aPrivacy in Statistical Databases$9772125
997   $aUNISA