Natasha Fernandes

43 papers A* 3A 3B 4Journal 27Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	B	`conf`	Composition Theorems for f-Differential Privacy. FoSSaCS Natasha Fernandes, Annabelle McIver, Parastoo Sadeghi
2026	J	`jnl`	Generalizable IoT Traffic Representations for Cross-Network Device Identification. CoRR Arunan Sivanathan, David Warren, Deepak Mishra, Sushmita Ruj, Natasha Fernandes, Quan Z. Sheng, Minh Tran, Ben Luo, Daniel Coscia, Gustavo Batista, Hassan Habibi Gharakaheili
2026	J	`jnl`	Real-Time and Trustworthy Classification of IoT Traffic Using Lightweight Deep Learning. IEEE Trans. Netw. Sci. Eng. Arunan Sivanathan, Deepak Mishra, Sushmita Ruj, Natasha Fernandes, Quan Z. Sheng, Minh Tran, Ben Luo, Daniel Coscia, Gustavo Batista, Hassan Habibi Gharakaheili
2025	J	`jnl`	A new measure for dynamic leakage based on quantitative information flow. CoRR Luigi D. C. Soares, Mário S. Alvim, Natasha Fernandes
2025	J	`jnl`	Comparing privacy notions for protection against reconstruction attacks in machine learning. CoRR Sayan Biswas, Mark Dras, Pedro Faustini, Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Parastoo Sadeghi
2025	J	`jnl`	Composition Theorems for f-Differential Privacy. CoRR Natasha Fernandes, Annabelle McIver, Parastoo Sadeghi
2025	J	`jnl`	Empirical Calibration and Metric Differential Privacy in Language Models. IEEE Access Pedro Faustini, Natasha Fernandes, Annabelle McIver, Mark Dras
2025	J	`jnl`	Empirical Calibration and Metric Differential Privacy in Language Models. CoRR Pedro Faustini, Natasha Fernandes, Annabelle McIver, Mark Dras
2025	J	`jnl`	What is the Cost of Differential Privacy for Deep Learning-Based Trajectory Generation? CoRR Erik Buchholz, Natasha Fernandes, David D. Nguyen, Alsharif Abuadbba, Surya Nepal, Salil S. Kanhere
2024	J	`jnl`	Bayes' capacity as a measure for reconstruction attacks in federated learning. CoRR Sayan Biswas, Mark Dras, Pedro Faustini, Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Parastoo Sadeghi
2024	A	`conf`	Explaining ∊ in Local Differential Privacy Through the Lens of Quantitative Information Flow. CSF Natasha Fernandes, Annabelle McIver, Parastoo Sadeghi
2024	—	`conf`	Formal Privacy Analyses for Open Banking. SBMF Luigi D. C. Soares, Mário S. Alvim, Di Bu, Natasha Fernandes, Yin Liao
2024	A*	`conf`	The Privacy-Utility Trade-off in the Topics API. CCS Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Gabriel H. Nunes
2024	J	`jnl`	The Privacy-Utility Trade-off in the Topics API. CoRR Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Gabriel H. Nunes
2023	A*	`conf`	A Novel Analysis of Utility in Privacy Pipelines, Using Kronecker Products and Quantitative Information Flow. CCS Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Carroll Morgan, Gabriel Henrique Nunes
2023	—	`conf`	A Quantitative Information Flow Analysis of the Topics API. WPES@CCS Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Gabriel Henrique Nunes
2023	J	`jnl`	A Quantitative Information Flow Analysis of the Topics API. CoRR Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Gabriel Henrique Nunes
2023	J	`jnl`	A novel analysis of utility in privacy pipelines, using Kronecker products and quantitative information flow. CoRR Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Carroll Morgan, Gabriel Henrique Nunes
2023	J	`jnl`	Quantitative Information Flow Techniques for Studying Optimality in Differential Privacy. ACM SIGLOG News Natasha Fernandes
2023	J	`jnl`	Universal optimality and robust utility bounds for metric differential privacy. J. Comput. Secur. Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Ming Ding
2022	J	`jnl`	A novel reconstruction attack on foreign-trade official statistics, with a Brazilian case study. CoRR Danilo Fabrino Favato, Gabriel Coutinho, Mário S. Alvim, Natasha Fernandes
2022	J	`jnl`	A novel reconstruction attack on foreign-trade official statistics, with a Brazilian case study. Proc. Priv. Enhancing Technol. Danilo Fabrino Favato, Gabriel Coutinho, Mário S. Alvim, Natasha Fernandes
2022	J	`jnl`	Directional Privacy for Deep Learning. CoRR Pedro Faustini, Natasha Fernandes, Annabelle McIver, Mark Dras
2022	J	`jnl`	Explaining epsilon in differential privacy through the lens of information theory. CoRR Natasha Fernandes, Annabelle McIver, Parastoo Sadeghi
2022	J	`jnl`	Flexible and scalable privacy assessment for very large datasets, with an application to official governmental microdata. CoRR Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Carroll Morgan, Gabriel Henrique Nunes
2022	J	`jnl`	Flexible and scalable privacy assessment for very large datasets, with an application to official governmental microdata. Proc. Priv. Enhancing Technol. Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Carroll Morgan, Gabriel Henrique Nunes
2022	B	`conf`	How to Develop an Intuition for Risk... and Other Invisible Phenomena (Invited Talk). CSL Natasha Fernandes, Annabelle McIver, Carroll Morgan
2022	A	`conf`	Universal Optimality and Robust Utility Bounds for Metric Differential Privacy. CSF Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Ming Ding
2022	J	`jnl`	Universal Optimality and Robust Utility Bounds for Metric Differential Privacy. CoRR Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Ming Ding
2021	—	`—`	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). Natasha Fernandes
2021	—	`conf`	Locality Sensitive Hashing with Extended Differential Privacy. ESORICS (2) Natasha Fernandes, Yusuke Kawamoto, Takao Murakami
2021	A*	`conf`	The Laplace Mechanism has optimal utility for differential privacy over continuous queries. LICS Natasha Fernandes, Annabelle McIver, Carroll Morgan
2021	J	`jnl`	The Laplace Mechanism has optimal utility for differential privacy over continuous queries. CoRR Natasha Fernandes, Annabelle McIver, Carroll Morgan
2020	J	`jnl`	Locality Sensitive Hashing with Extended Differential Privacy. CoRR Natasha Fernandes, Yusuke Kawamoto, Takao Murakami
2020	B	`conf`	On Privacy and Accuracy in Data Releases (Invited Paper). CONCUR Mário S. Alvim, Natasha Fernandes, Annabelle McIver, Gabriel Henrique Nunes
2020	J	`jnl`	Refinement Orders for Quantitative Information Flow and Differential Privacy. J. Cybersecur. Priv. Konstantinos Chatzikokolakis, Natasha Fernandes, Catuscia Palamidessi
2019	A	`conf`	Comparing Systems: Max-Case Refinement Orders and Application to Differential Privacy. CSF Konstantinos Chatzikokolakis, Natasha Fernandes, Catuscia Palamidessi
2019	—	`conf`	Generalised Differential Privacy for Text Document Processing. POST Natasha Fernandes, Mark Dras, Annabelle McIver
2019	—	`conf`	Utility-Preserving Privacy Mechanisms for Counting Queries. Models, Languages, and Tools for Concurrent and Distributed Programming Natasha Fernandes, Lefki Kacem, Catuscia Palamidessi
2019	J	`jnl`	Utility-Preserving Privacy Mechanisms for Counting Queries. CoRR Natasha Fernandes, Lefki Kacem, Catuscia Palamidessi
2018	J	`jnl`	Author Obfuscation Using Generalised Differential Privacy. CoRR Natasha Fernandes, Mark Dras, Annabelle McIver
2018	J	`jnl`	Generalised Differential Privacy for Text Document Processing. CoRR Natasha Fernandes, Mark Dras, Annabelle McIver
2018	B	`conf`	Processing Text for Privacy: An Information Flow Perspective. FM Natasha Fernandes, Mark Dras, Annabelle McIver