Copertina

Over-the-Air Collaborative Inference with Feature Differential Privacy

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Seif, Mohamed, Nie, Yuqi, Goldsmith, Andrea, Poor, Vincent
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Information Theory Cryptography and Security
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Collaborative Inference over Wireless Channels with Feature Differential Privacy
di: Seif, Mohamed, et al.
Pubblicazione: (2024)

Differentially Private Spectral Graph Clustering: Balancing Privacy, Accuracy, and Efficiency
di: Koskela, Antti, et al.
Pubblicazione: (2025)

Differentially Private Online Community Detection for Censored Block Models: Algorithms and Fundamental Limits
di: Seif, Mohamed, et al.
Pubblicazione: (2024)

Adversary-Aware Private Inference over Wireless Channels
di: Seif, Mohamed, et al.
Pubblicazione: (2025)

On the Price of Differential Privacy for Spectral Clustering over Stochastic Block Models
di: Koskela, Antti, et al.
Pubblicazione: (2025)

Protecting Human Activity Signatures in Compressed IEEE 802.11 CSI Feedback
di: Seif, Mohamed, et al.
Pubblicazione: (2025)

Private Collaborative Edge Inference via Over-the-Air Computation
di: Yilmaz, Selim F., et al.
Pubblicazione: (2024)

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference
di: Liu, Rongke, et al.
Pubblicazione: (2025)

Composition Theorems for f-Differential Privacy
di: Fernandes, Natasha, et al.
Pubblicazione: (2025)

On Improving the Composition Privacy Loss in Differential Privacy for Fixed Estimation Error
di: Rameshwar, V. Arvind, et al.
Pubblicazione: (2024)

The Hidden Cost of Correlation: Rethinking Privacy Leakage in Local Differential Privacy
di: Jayawardana, Sandaru, et al.
Pubblicazione: (2025)

Generalized Rainbow Differential Privacy
di: Gu, Yuzhou, et al.
Pubblicazione: (2023)

Differentially Private Over-the-Air Federated Learning Over MIMO Fading Channels
di: Liu, Hang, et al.
Pubblicazione: (2023)

Dobrushin Coefficients of Private Mechanisms Beyond Local Differential Privacy
di: Grosse, Leonhard, et al.
Pubblicazione: (2026)

Evaluating Differential Privacy on Correlated Datasets Using Pointwise Maximal Leakage
di: Saeidian, Sara, et al.
Pubblicazione: (2025)

Strict Optimality of Frequency and Distribution Estimation Under Local Differential Privacy
di: Pan, Mingen
Pubblicazione: (2026)

Rao Differential Privacy
di: Soto, Carlos
Pubblicazione: (2025)

Fundamental Limit of Discrete Distribution Estimation under Utility-Optimized Local Differential Privacy
di: Yoon, Sun-Moon, et al.
Pubblicazione: (2025)

Inference Privacy: Properties and Mechanisms
di: Tian, Fengwei, et al.
Pubblicazione: (2024)

Breaking the Communication-Privacy-Accuracy Tradeoff with $f$-Differential Privacy
di: Jin, Richeng, et al.
Pubblicazione: (2023)

Exploring the Privacy-Energy Consumption Tradeoff for Split Federated Learning
di: Lee, Joohyung, et al.
Pubblicazione: (2023)

Spectrum Breathing: Protecting Over-the-Air Federated Learning Against Interference
di: Wang, Zhanwei, et al.
Pubblicazione: (2023)

Privacy for Fairness: Information Obfuscation for Fair Representation Learning with Local Differential Privacy
di: Xie, Songjie, et al.
Pubblicazione: (2024)

Concentrated Differential Privacy for Bandits
di: Azize, Achraf, et al.
Pubblicazione: (2023)

When Does Quantum Differential Privacy Compose?
di: Alabi, Daniel, et al.
Pubblicazione: (2026)

Correlated Privacy Mechanisms for Differentially Private Distributed Mean Estimation
di: Vithana, Sajani, et al.
Pubblicazione: (2024)

Information Density Bounds for Privacy
di: Saeidian, Sara, et al.
Pubblicazione: (2024)

Realisation-Level Privacy Filtering
di: Taylor, Sophie, et al.
Pubblicazione: (2026)

Privacy Against Agnostic Inference Attacks in Vertical Federated Learning
di: Varasteh, Morteza
Pubblicazione: (2023)

Meeting Utility Constraints in Differential Privacy: A Privacy-Boosting Approach
di: Jiang, Bo, et al.
Pubblicazione: (2024)

Concurrent Composition for Interactive Differential Privacy with Adaptive Privacy-Loss Parameters
di: Haney, Samuel, et al.
Pubblicazione: (2023)

Approximation of Pufferfish Privacy for Gaussian Priors
di: Ding, Ni
Pubblicazione: (2024)

Balancing Privacy and Utility in Correlated Data: A Study of Bayesian Differential Privacy
di: Lange, Martin, et al.
Pubblicazione: (2025)

Outer Bounds on the CEO Problem with Privacy Constraints
di: Yachongka, Vamoua, et al.
Pubblicazione: (2023)

Privacy Mechanism Design based on Empirical Distributions
di: Grosse, Leonhard, et al.
Pubblicazione: (2025)

Local Differential Privacy with Correlated Noise Achieves Central-DP Optimal Cost
di: Pathegama, Madhura, et al.
Pubblicazione: (2026)

Sample Complexity Bounds for Scalar Parameter Estimation Under Quantum Differential Privacy
di: Farokhi, Farhad
Pubblicazione: (2025)

Achieving Dalenius' Goal of Data Privacy with Practical Assumptions
di: Wu, Genqiang, et al.
Pubblicazione: (2017)

Optimal Regret of Bernoulli Bandits under Global Differential Privacy
di: Azize, Achraf, et al.
Pubblicazione: (2025)

On Spatial-Provenance Recovery in Wireless Networks with Relaxed-Privacy Constraints
di: Bansal, Manish, et al.
Pubblicazione: (2025)