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Title
Japanese: 
English:Approximate Span Liftings: Compositional Semantics for Relaxations of Differential Privacy 
Author
Japanese: 佐藤 哲也, Gilles Barthe, Marco Gaboardi, Justin Hsu, Shin-ya Katsumata.  
English: Tetsuya Sato, Gilles Barthe, Marco Gaboardi, Justin Hsu, Shin-ya Katsumata.  
Language English 
Journal/Book name
Japanese: 
English:2019 34th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS) 
Volume, Number, Page        
Published date Aug. 5, 2020 
Publisher
Japanese: 
English:IEEE 
Conference name
Japanese:LICS 2019 
English:34th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS) 
Conference site
Japanese: 
English:Vancouver, BC 
Official URL https://ieeexplore.ieee.org/document/8785668
 
DOI https://doi.org/10.1109/LICS.2019.8785668
Abstract We develop new abstractions for reasoning about relaxations of differential privacy: Rényi differential privacy, zero-concentrated differential privacy, and truncated concentrated differential privacy, which express different bounds on statistical divergences between two output probability distributions. In order to reason about such properties compositionally, we introduce approximate span-lifting, a novel construction extending the approximate relational lifting approaches previously developed for standard differential privacy to a more general class of divergences, and also to continuous distributions. As an application, we develop a program logic based on approximate span-liftings capable of proving relaxations of differential privacy and other statistical divergence properties.

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