Beyond Epsilon: A Principled QIF Framework for Local Differential Privacy
Fuente:
arXiv
Saved in:
| Main Authors: | Gonze, Ramon G., Fernandes, Natasha, Arcolezi, Heber H., Palamidessi, Catuscia, Bielova, Nataliia |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Systematic and Formal Study of the Impact of Local Differential Privacy on Fairness: Preliminary Results
by: Makhlouf, Karima, et al.
Published: (2024)
by: Makhlouf, Karima, et al.
Published: (2024)
On the Impact of Multi-dimensional Local Differential Privacy on Fairness
by: Makhlouf, Karima, et al.
Published: (2023)
by: Makhlouf, Karima, et al.
Published: (2023)
Self-Defense: Optimal QIF Solutions and Application to Website Fingerprinting
by: Athanasiou, Andreas, et al.
Published: (2024)
by: Athanasiou, Andreas, et al.
Published: (2024)
Causal Discovery Under Local Privacy
by: Binkytė, Rūta, et al.
Published: (2023)
by: Binkytė, Rūta, et al.
Published: (2023)
Revisiting Locally Differentially Private Protocols: Towards Better Trade-offs in Privacy, Utility, and Attack Resistance
by: Arcolezi, Héber H., et al.
Published: (2025)
by: Arcolezi, Héber H., et al.
Published: (2025)
Tight Differential Privacy Guarantees for the Shuffle Model with $k$-Randomized Response
by: Biswas, Sayan, et al.
Published: (2022)
by: Biswas, Sayan, et al.
Published: (2022)
Revealing the True Cost of Locally Differentially Private Protocols: An Auditing Perspective
by: Arcolezi, Héber H., et al.
Published: (2023)
by: Arcolezi, Héber H., et al.
Published: (2023)
Estimating the True Distribution of Data Collected with Randomized Response
by: Pinzón, Carlos Antonio, et al.
Published: (2026)
by: Pinzón, Carlos Antonio, et al.
Published: (2026)
Private Frequency Estimation Via Residue Number Systems
by: Arcolezi, Héber H.
Published: (2025)
by: Arcolezi, Héber H.
Published: (2025)
Jeffrey's update rule as a minimizer of Kullback-Leibler divergence
by: Pinzón, Carlos, et al.
Published: (2025)
by: Pinzón, Carlos, et al.
Published: (2025)
Protection against Source Inference Attacks in Federated Learning
by: Athanasiou, Andreas, et al.
Published: (2026)
by: Athanasiou, Andreas, et al.
Published: (2026)
Protection against Source Inference Attacks in Federated Learning using Unary Encoding and Shuffling
by: Athanasiou, Andreas, et al.
Published: (2024)
by: Athanasiou, Andreas, et al.
Published: (2024)
On the Consistency and Performance of the Iterative Bayesian Update
by: ElSalamouny, Ehab, et al.
Published: (2025)
by: ElSalamouny, Ehab, et al.
Published: (2025)
You Can't Trust Your Tag Neither: Privacy Leaks and Potential Legal Violations within the Google Tag Manager
by: Mertens, Gilles, et al.
Published: (2023)
by: Mertens, Gilles, et al.
Published: (2023)
Bayes Security: A Not So Average Metric
by: Chatzikokolakis, Konstantinos, et al.
Published: (2020)
by: Chatzikokolakis, Konstantinos, et al.
Published: (2020)
Information Leakage Envelopes
by: Saeidian, Sara, et al.
Published: (2026)
by: Saeidian, Sara, et al.
Published: (2026)
Mitigating Membership Inference Vulnerability in Personalized Federated Learning
by: Jung, Kangsoo, et al.
Published: (2025)
by: Jung, Kangsoo, et al.
Published: (2025)
Understanding Disclosure Risk in Differential Privacy with Applications to Noise Calibration and Auditing (Extended Version)
by: Guerra-Balboa, Patricia, et al.
Published: (2026)
by: Guerra-Balboa, Patricia, et al.
Published: (2026)
A privacy preserving querying mechanism with high utility for electric vehicles
by: Atmaca, Ugur Ilker, et al.
Published: (2022)
by: Atmaca, Ugur Ilker, et al.
Published: (2022)
How Tough Is Location Anonymization? Re-identifying 100K Real-User Trajectories in Japan
by: Mishra, Abhishek Kumar, et al.
Published: (2025)
by: Mishra, Abhishek Kumar, et al.
Published: (2025)
Measuring Compliance of Consent Revocation on the Web
by: Kancherla, Gayatri Priyadarsini, et al.
Published: (2024)
by: Kancherla, Gayatri Priyadarsini, et al.
Published: (2024)
Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks
by: Díaz, Judith Sáinz-Pardo, et al.
Published: (2025)
by: Díaz, Judith Sáinz-Pardo, et al.
Published: (2025)
Comparing privacy notions for protection against reconstruction attacks in machine learning
by: Biswas, Sayan, et al.
Published: (2025)
by: Biswas, Sayan, et al.
Published: (2025)
Bayes' capacity as a measure for reconstruction attacks in federated learning
by: Biswas, Sayan, et al.
Published: (2024)
by: Biswas, Sayan, et al.
Published: (2024)
Composition Theorems for f-Differential Privacy
by: Fernandes, Natasha, et al.
Published: (2025)
by: Fernandes, Natasha, et al.
Published: (2025)
Fair Play for Individuals, Foul Play for Groups? Auditing Anonymization's Impact on ML Fairness
by: Arcolezi, Héber H., et al.
Published: (2025)
by: Arcolezi, Héber H., et al.
Published: (2025)
Empirical Calibration and Metric Differential Privacy in Language Models
by: Faustini, Pedro, et al.
Published: (2025)
by: Faustini, Pedro, et al.
Published: (2025)
Nob-MIAs: Non-biased Membership Inference Attacks Assessment on Large Language Models with Ex-Post Dataset Construction
by: Eichler, Cédric, et al.
Published: (2024)
by: Eichler, Cédric, et al.
Published: (2024)
Feedback to the European Data Protection Board's Guidelines 2/2023 on Technical Scope of Art. 5(3) of ePrivacy Directive
by: Santos, Cristiana, et al.
Published: (2024)
by: Santos, Cristiana, et al.
Published: (2024)
The Privacy-Utility Trade-off in the Topics API
by: Alvim, Mário S., et al.
Published: (2024)
by: Alvim, Mário S., et al.
Published: (2024)
PEEL: A Poisoning-Exposing Encoding Theoretical Framework for Local Differential Privacy
by: Shuai, Lisha, et al.
Published: (2025)
by: Shuai, Lisha, et al.
Published: (2025)
Dobrushin Coefficients of Private Mechanisms Beyond Local Differential Privacy
by: Grosse, Leonhard, et al.
Published: (2026)
by: Grosse, Leonhard, et al.
Published: (2026)
Local Distance Query with Differential Privacy
by: Sheng, Weihong, et al.
Published: (2025)
by: Sheng, Weihong, et al.
Published: (2025)
What is the Cost of Differential Privacy for Deep Learning-Based Trajectory Generation?
by: Buchholz, Erik, et al.
Published: (2025)
by: Buchholz, Erik, et al.
Published: (2025)
MTSP-LDP: A Framework for Multi-Task Streaming Data Publication under Local Differential Privacy
by: Liu, Chang, et al.
Published: (2025)
by: Liu, Chang, et al.
Published: (2025)
A Unifying Privacy Analysis Framework for Unknown Domain Algorithms in Differential Privacy
by: Rogers, Ryan
Published: (2023)
by: Rogers, Ryan
Published: (2023)
Beyond Theoretical Bounds: Empirical Privacy Loss Calibration for Text Rewriting Under Local Differential Privacy
by: Li, Weijun, et al.
Published: (2026)
by: Li, Weijun, et al.
Published: (2026)
A Framework for Differential Privacy Against Timing Attacks
by: Ratliff, Zachary, et al.
Published: (2024)
by: Ratliff, Zachary, et al.
Published: (2024)
Local Layer-wise Differential Privacy in Federated Learning
by: Li, Yunbo, et al.
Published: (2026)
by: Li, Yunbo, et al.
Published: (2026)
Mitigating Data Poisoning Attacks to Local Differential Privacy
by: Li, Xiaolin, et al.
Published: (2025)
by: Li, Xiaolin, et al.
Published: (2025)
Similar Items
-
A Systematic and Formal Study of the Impact of Local Differential Privacy on Fairness: Preliminary Results
by: Makhlouf, Karima, et al.
Published: (2024) -
On the Impact of Multi-dimensional Local Differential Privacy on Fairness
by: Makhlouf, Karima, et al.
Published: (2023) -
Self-Defense: Optimal QIF Solutions and Application to Website Fingerprinting
by: Athanasiou, Andreas, et al.
Published: (2024) -
Causal Discovery Under Local Privacy
by: Binkytė, Rūta, et al.
Published: (2023) -
Revisiting Locally Differentially Private Protocols: Towards Better Trade-offs in Privacy, Utility, and Attack Resistance
by: Arcolezi, Héber H., et al.
Published: (2025)