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Guide to differential privacy modificationsa taxonomy of variants and extensions /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Guide to differential privacy modificationsby Balazs Pejo, Damien Desfontaines.
其他題名:	a taxonomy of variants and extensions /
作者:	Pejo, Balazs.
其他作者:	Desfontaines, Damien.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	viii, 89 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Computer security.
電子資源:	https://doi.org/10.1007/978-3-030-96398-9
ISBN:	9783030963989$q(electronic bk.)

Guide to differential privacy modificationsa taxonomy of variants and extensions /
Pejo, Balazs.

Guide to differential privacy modificationsa taxonomy of variants and extensions /[electronic resource] :by Balazs Pejo, Damien Desfontaines. - Cham :Springer International Publishing :2022. - viii, 89 p. :ill., digital ;24 cm. - 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$q(electronic bk.)

Standard No.: 10.1007/978-3-030-96398-9doiSubjects--Topical Terms:

184416
Computer security.

LC Class. No.: QA76.9.A25 / P45 2022

Dewey Class. No.: 005.8

Guide to differential privacy modificationsa taxonomy of variants and extensions /
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505 0 $a 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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