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Guide to Differential Privacy Modifications = A Taxonomy of Variants and Extensions /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Guide to Differential Privacy Modifications/ by Balázs Pejó, Damien Desfontaines.
其他題名:
A Taxonomy of Variants and Extensions /
作者:
Pejó, Balázs.
其他作者:
Desfontaines, Damien.
面頁冊數:
VIII, 89 p. 2 illus.online resource. :
Contained By:
Springer Nature eBook
標題:
Cryptology. -
電子資源:
https://doi.org/10.1007/978-3-030-96398-9
ISBN:
9783030963989
Guide to Differential Privacy Modifications = A Taxonomy of Variants and Extensions /
Pejó, Balázs.
Guide to Differential Privacy Modifications
A Taxonomy of Variants and Extensions /[electronic resource] :by Balázs Pejó, Damien Desfontaines. - 1st ed. 2022. - VIII, 89 p. 2 illus.online resource. - SpringerBriefs in Computer Science,2191-5776. - SpringerBriefs in Computer Science,.
1. 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.
Shortly 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 collecting existing ones.
ISBN: 9783030963989
Standard No.: 10.1007/978-3-030-96398-9doiSubjects--Topical Terms:
1211076
Cryptology.
LC Class. No.: QA76.9.A25
Dewey Class. No.: 005.8
Guide to Differential Privacy Modifications = A Taxonomy of Variants and Extensions /
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1. 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.
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Shortly 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 collecting existing ones.
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