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Refinement Orders for Quantitative Information Flow and Differential PrivacyJournal of Cybersecurity and Privacy, 2020, 1, pp.40 - 77. ⟨10.3390/jcp1010004⟩
Journal articles
hal-03091754v1
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Utility-Preserving Privacy Mechanisms for Counting QueriesMichele Boreale; Flavio Corradini; Michele Loreti; Rosario Pugliese. Models, Languages and Tools for Concurrent and Distributed Programming, 11665, Springer, pp.487-495, 2019, Lecture Notes in Computer Science, ⟨10.1007/978-3-030-21485-2_27⟩
Book sections
hal-02169218v1
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Locality Sensitive Hashing with Extended Differential PrivacyESORICS 2021 - 26th European Symposium on Research in Computer Security, Oct 2021, Darmstadt / Virtual, Germany. pp.563--583, ⟨10.1007/978-3-030-88428-4_28⟩
Conference papers
hal-03319774v1
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Differential Privacy for Metric Spaces: Information-Theoretic Models for Privacy and Utility with New Applications to Metric DomainsInformation Theory [cs.IT]. École Polytechnique Paris; Macquarie University, 2021. English. ⟨NNT : ⟩
Theses
tel-03344320v1
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Comparing systems: max-case refinement orders and application to differential privacyCSF 2019 - 32nd IEEE Computer Security Foundations Symposium, Jun 2019, Hoboken, United States. pp.442--457, ⟨10.1109/CSF.2019.00037⟩
Conference papers
hal-02126848v1
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