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タイトル
和文: 
英文:Relational *-Liftings for Differential Privacy. 
著者
和文: Gilles Barthe, Thomas Espitau, Justin Hsu, 佐藤 哲也, Pierre-Yves Strub.  
英文: Gilles Barthe, Thomas Espitau, Justin Hsu, Tetsuya Sato, Pierre-Yves Strub.  
言語 English 
掲載誌/書名
和文: 
英文:Logical Methods in Computer Science 
巻, 号, ページ Volume 15    Issue 154   
出版年月 2019年12月 
出版者
和文: 
英文: 
会議名称
和文: 
英文: 
開催地
和文: 
英文: 
公式リンク https://lmcs.episciences.org/5989
 
DOI https://doi.org/10.23638/LMCS-15(4:18)2019
アブストラクト Recent developments in formal verification have identified approximate liftings (also known as approximate couplings) as a clean, compositional abstraction for proving differential privacy. This construction can be defined in two styles. Earlier definitions require the existence of one or more witness distributions, while a recent definition by Sato uses universal quantification over all sets of samples. These notions have each have their own strengths: the universal version is more general than the existential ones, while existential liftings are known to satisfy more precise composition principles. We propose a novel, existential version of approximate lifting, called ⋆-lifting, and show that it is equivalent to Sato's construction for discrete probability measures. Our work unifies all known notions of approximate lifting, yielding cleaner properties, more general constructions, and more precise composition theorems for both styles of lifting, enabling richer proofs of differential privacy. We also clarify the relation between existing definitions of approximate lifting, and consider more general approximate liftings based on f-divergences.

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