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ORCIDNatasha Fernandes
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2020 – today
- 2024
[c12]Natasha Fernandes, Annabelle McIver, Parastoo Sadeghi:
Explaining ∊ in Local Differential Privacy Through the Lens of Quantitative Information Flow. CSF 2024: 419-432- [i14]Sayan Biswas, Mark Dras, Pedro Faustini, Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Parastoo Sadeghi:
Bayes' capacity as a measure for reconstruction attacks in federated learning. CoRR abs/2406.13569 (2024) - [i13]Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Gabriel H. Nunes:
The Privacy-Utility Trade-off in the Topics API. CoRR abs/2406.15309 (2024) - 2023
- [j5]Natasha Fernandes
, Annabelle McIver, Catuscia Palamidessi, Ming Ding:
Universal optimality and robust utility bounds for metric differential privacy. J. Comput. Secur. 31(5): 539-580 (2023) - [j4]Natasha Fernandes:
Quantitative Information Flow Techniques for Studying Optimality in Differential Privacy. ACM SIGLOG News 10(1): 4-22 (2023) - [c11]Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Carroll Morgan, Gabriel Henrique Nunes:
A Novel Analysis of Utility in Privacy Pipelines, Using Kronecker Products and Quantitative Information Flow. CCS 2023: 1718-1731 - [c10]Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Gabriel Henrique Nunes:
A Quantitative Information Flow Analysis of the Topics API. WPES@CCS 2023: 123-127 - [i12]Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Carroll Morgan, Gabriel Henrique Nunes:
A novel analysis of utility in privacy pipelines, using Kronecker products and quantitative information flow. CoRR abs/2308.11110 (2023) - [i11]Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Gabriel Henrique Nunes:
A Quantitative Information Flow Analysis of the Topics API. CoRR abs/2309.14746 (2023) - 2022
- [j3]Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Carroll Morgan, Gabriel Henrique Nunes:
Flexible and scalable privacy assessment for very large datasets, with an application to official governmental microdata. Proc. Priv. Enhancing Technol. 2022(4): 378-399 (2022) - [j2]Danilo Fabrino Favato, Gabriel Coutinho, Mário S. Alvim, Natasha Fernandes:
A novel reconstruction attack on foreign-trade official statistics, with a Brazilian case study. Proc. Priv. Enhancing Technol. 2022(4): 608-625 (2022) - [c9]Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Ming Ding:
Universal Optimality and Robust Utility Bounds for Metric Differential Privacy. CSF 2022: 348-363 - [c8]Natasha Fernandes, Annabelle McIver, Carroll Morgan:
How to Develop an Intuition for Risk... and Other Invisible Phenomena (Invited Talk). CSL 2022: 2:1-2:14 - [i10]Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Carroll Morgan, Gabriel Henrique Nunes:
Flexible and scalable privacy assessment for very large datasets, with an application to official governmental microdata. CoRR abs/2204.13734 (2022) - [i9]Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Ming Ding:
Universal Optimality and Robust Utility Bounds for Metric Differential Privacy. CoRR abs/2205.01258 (2022) - [i8]Danilo Fabrino Favato, Gabriel Coutinho, Mário S. Alvim, Natasha Fernandes:
A novel reconstruction attack on foreign-trade official statistics, with a Brazilian case study. CoRR abs/2206.06493 (2022) - [i7]Natasha Fernandes, Annabelle McIver, Parastoo Sadeghi:
Explaining epsilon in differential privacy through the lens of information theory. CoRR abs/2210.12916 (2022) - [i6]Pedro Faustini, Natasha Fernandes, Annabelle McIver, Mark Dras:
Directional Privacy for Deep Learning. CoRR abs/2211.04686 (2022) - 2021
- [b1]Natasha Fernandes:
Differential Privacy for Metric Spaces: Information-Theoretic Models for Privacy and Utility with New Applications to Metric Domains. (Confidentialité différentielle pour les espaces métriques: modèles théoriques de l'information pour la confidentialité et l'utilité avec de nouvelles applications aux domaines métriques). École Polytechnique, Palaiseau, France, 2021 - [c7]Natasha Fernandes, Yusuke Kawamoto, Takao Murakami:
Locality Sensitive Hashing with Extended Differential Privacy. ESORICS (2) 2021: 563-583 - [c6]Natasha Fernandes, Annabelle McIver, Carroll Morgan:
The Laplace Mechanism has optimal utility for differential privacy over continuous queries. LICS 2021: 1-12 - [i5]Natasha Fernandes, Annabelle McIver, Carroll Morgan:
The Laplace Mechanism has optimal utility for differential privacy over continuous queries. CoRR abs/2105.07176 (2021) - 2020
- [j1]Konstantinos Chatzikokolakis, Natasha Fernandes, Catuscia Palamidessi:
Refinement Orders for Quantitative Information Flow and Differential Privacy. J. Cybersecur. Priv. 1(1): 40-77 (2020) - [c5]Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Gabriel Henrique Nunes:
On Privacy and Accuracy in Data Releases (Invited Paper). CONCUR 2020: 1:1-1:18 - [i4]Natasha Fernandes, Yusuke Kawamoto, Takao Murakami:
Locality Sensitive Hashing with Extended Differential Privacy. CoRR abs/2010.09393 (2020)
2010 – 2019
- 2019
- [c4]Natasha Fernandes, Lefki Kacem, Catuscia Palamidessi:
Utility-Preserving Privacy Mechanisms for Counting Queries. Models, Languages, and Tools for Concurrent and Distributed Programming 2019: 487-495 - [c3]Konstantinos Chatzikokolakis, Natasha Fernandes, Catuscia Palamidessi:
Comparing Systems: Max-Case Refinement Orders and Application to Differential Privacy. CSF 2019: 442-457 - [c2]Natasha Fernandes, Mark Dras, Annabelle McIver:
Generalised Differential Privacy for Text Document Processing. POST 2019: 123-148 - [i3]Natasha Fernandes, Lefki Kacem, Catuscia Palamidessi:
Utility-Preserving Privacy Mechanisms for Counting Queries. CoRR abs/1906.12147 (2019) - 2018
- [c1]Natasha Fernandes, Mark Dras, Annabelle McIver:
Processing Text for Privacy: An Information Flow Perspective. FM 2018: 3-21 - [i2]Natasha Fernandes, Mark Dras, Annabelle McIver:
Author Obfuscation Using Generalised Differential Privacy. CoRR abs/1805.08866 (2018) - [i1]Natasha Fernandes, Mark Dras, Annabelle McIver:
Generalised Differential Privacy for Text Document Processing. CoRR abs/1811.10256 (2018)
Coauthor Index
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last updated on 2024-10-07 22:11 CEST by the dblp team
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