000 | 03393nam a22005775i 4500 | ||
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001 | 978-3-030-96398-9 | ||
003 | DE-He213 | ||
005 | 20240423125542.0 | ||
007 | cr nn 008mamaa | ||
008 | 220409s2022 sz | s |||| 0|eng d | ||
020 |
_a9783030963989 _9978-3-030-96398-9 |
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024 | 7 |
_a10.1007/978-3-030-96398-9 _2doi |
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050 | 4 | _aQA76.9.A25 | |
050 | 4 | _aJC596-596.2 | |
072 | 7 |
_aURD _2bicssc |
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072 | 7 |
_aCOM060040 _2bisacsh |
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072 | 7 |
_aURD _2thema |
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082 | 0 | 4 |
_a005.8 _223 |
082 | 0 | 4 |
_a323.448 _223 |
100 | 1 |
_aPejó, Balázs. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aGuide to Differential Privacy Modifications _h[electronic resource] : _bA Taxonomy of Variants and Extensions / _cby Balázs Pejó, Damien Desfontaines. |
250 | _a1st ed. 2022. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2022. |
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300 |
_aVIII, 89 p. 2 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSpringerBriefs in Computer Science, _x2191-5776 |
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505 | 0 | _a1. Introduction -- 2. Differential Privacy -- 3. Quantification of privacy loss -- 4. Neighborhood definition (N) -- 5. Variation of privacy loss (V) -- 6. Background knowledge (B) -- 7. Change in formalism (F) -- 8. Relativization of the knowledge gain (R) -- 9. Computational power (C) -- 10. Summarizing table -- 11. Scope and related work -- 12. Conclusion. | |
520 | _aShortly after it was first introduced in 2006, differential privacy became the flagship data privacy definition. Since then, numerous variants and extensions were proposed to adapt it to different scenarios and attacker models. In this work, we propose a systematic taxonomy of these variants and extensions. We list all data privacy definitions based on differential privacy, and partition them into seven categories, depending on which aspect of the original definition is modified. These categories act like dimensions: Variants from the same category cannot be combined, but variants from different categories can be combined to form new definitions. We also establish a partial ordering of relative strength between these notions by summarizing existing results. Furthermore, we list which of these definitions satisfy some desirable properties, like composition, post-processing, and convexity by either providing a novel proof or collectingexisting ones. | ||
650 | 0 |
_aData protection _xLaw and legislation. |
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650 | 0 | _aData protection. | |
650 | 0 | _aCryptography. | |
650 | 0 | _aData encryption (Computer science). | |
650 | 1 | 4 | _aPrivacy. |
650 | 2 | 4 | _aData and Information Security. |
650 | 2 | 4 | _aCryptology. |
700 | 1 |
_aDesfontaines, Damien. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783030963972 |
776 | 0 | 8 |
_iPrinted edition: _z9783030963996 |
830 | 0 |
_aSpringerBriefs in Computer Science, _x2191-5776 |
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856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-96398-9 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
_c179204 _d179204 |