Privacy Against Statistical Inference

8 October 2012

Papers citing "Privacy Against Statistical Inference"

50 / 83 papers shown

Title
Learning-based Privacy-Preserving Graph Publishing Against Sensitive Link Inference Attacks Yucheng Wu Yuncong Yang Xiao Han Leye Wang Junjie Wu 26 0 0 23 Jul 2025
Breaking the Gaussian Barrier: Residual-PAC Privacy for Automatic Privatization Tao Zhang Yevgeniy Vorobeychik 108 1 0 06 Jun 2025
Analyzing Inference Privacy Risks Through Gradients in Machine Learning Zhuohang Li Andrew Lowy Jing Liu T. Koike-Akino K. Parsons Bradley Malin Ye Wang FedML 108 2 0 29 Aug 2024
Information Density Bounds for Privacy Sara Saeidian Leonhard Grosse Parastoo Sadeghi Mikael Skoglund T. Oechtering 118 1 0 01 Jul 2024
Federated Graph Condensation with Information Bottleneck Principles Bo Yan DD FedML 100 5 0 07 May 2024
Maximal $α$ -Leakage for Quantum Privacy Mechanisms Bo-Yu Yang Hsuan Yu Hao-Chung Cheng 91 0 0 21 Mar 2024
Quantifying Privacy via Information Density Leonhard Grosse Sara Saeidian Parastoo Sadeghi T. Oechtering Mikael Skoglund 53 4 0 20 Feb 2024
Privacy for Fairness: Information Obfuscation for Fair Representation Learning with Local Differential Privacy Songjie Xie Youlong Wu Jiaxuan Li Ming Ding Khaled B. Letaief AAML 86 1 0 16 Feb 2024
Approximation of Pufferfish Privacy for Gaussian Priors Ni Ding FedML 65 0 0 22 Jan 2024
Online Context-aware Data Release with Sequence Information Privacy Bo Jiang Ming Li Ravi Tandon 72 2 0 26 Jul 2023
A Meta-learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning Xiaojin Zhang Yan Kang Lixin Fan Kai Chen Qiang Yang FedML 108 8 0 28 May 2023
Theoretically Principled Federated Learning for Balancing Privacy and Utility Xiaojin Zhang Wenjie Li Kai Chen Shutao Xia Qian Yang FedML 96 10 0 24 May 2023
Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion Xiaojin Zhang Kai Chen Qian Yang FedML 104 6 0 07 May 2023
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information Kiwan Maeng Chuan Guo Sanjay Kariyappa G. E. Suh 109 9 0 06 May 2023
Optimizing Privacy, Utility and Efficiency in Constrained Multi-Objective Federated Learning Yan Kang Hanlin Gu Xingxing Tang Yuanqin He Yuzhu Zhang Jinnan He Yuxing Han Lixin Fan Kai Chen Qiang Yang FedML 170 19 0 29 Apr 2023
Pointwise Maximal Leakage on General Alphabets Sara Saeidian Giulia Cervia T. Oechtering Mikael Skoglund 63 5 0 16 Apr 2023
A Game-theoretic Framework for Privacy-preserving Federated Learning Xiaojin Zhang Lixin Fan Si-Yi Wang Wenjie Li Kai Chen Qiang Yang FedML 100 5 0 11 Apr 2023
Probably Approximately Correct Federated Learning Xiaojin Zhang Anbu Huang Lixin Fan Kai Chen Qiang Yang FedML 190 5 0 10 Apr 2023
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity Faisal Hamman Jiahao Chen Sanghamitra Dutta 114 9 0 03 Nov 2022
Explaining epsilon in local differential privacy through the lens of quantitative information flow Natasha Fernandes Annabelle McIver Parastoo Sadeghi PILM 64 2 0 24 Oct 2022
Trading Off Privacy, Utility and Efficiency in Federated Learning Xiaojin Zhang Yan Kang Kai Chen Lixin Fan Qiang Yang FedML 179 60 0 01 Sep 2022
Deep Joint Source-Channel and Encryption Coding: Secure Semantic Communications Tze-Yang Tung Deniz Gunduz BDL 139 56 0 19 Aug 2022
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility Behrooz Razeghi Flavio du Pin Calmon Deniz Gunduz Svyatoslav Voloshynovskiy 89 16 0 11 Jul 2022
Classification Utility, Fairness, and Compactness via Tunable Information Bottleneck and Rényi Measures A. Gronowski William Paul F. Alajaji Bahman Gharesifard Philippe Burlina FaML 129 5 0 20 Jun 2022
No Free Lunch Theorem for Security and Utility in Federated Learning Xiaojin Zhang Hanlin Gu Lixin Fan Kai Chen Qiang Yang FedML 115 68 0 11 Mar 2022
Active Privacy-Utility Trade-off Against Inference in Time-Series Data Sharing Ece Naz Erdemir Pier Luigi Dragotti Deniz Gunduz 92 9 0 11 Feb 2022
Lossy Compression of Noisy Data for Private and Data-Efficient Learning Berivan Isik Tsachy Weissman 145 3 0 07 Feb 2022
Kantorovich Mechanism for Pufferfish Privacy Ni Ding 102 3 0 19 Jan 2022
HyObscure: Hybrid Obscuring for Privacy-Preserving Data Publishing Xiao Han Yuncong Yang Junjie Wu 74 3 0 15 Dec 2021
Privacy-Aware Communication Over a Wiretap Channel with Generative Networks Ece Naz Erdemir Pier Luigi Dragotti Deniz Gunduz 109 26 0 08 Oct 2021
Subset Privacy: Draw from an Obfuscated Urn G. Wang Jie Ding 78 2 0 02 Jul 2021
A Survey of Privacy Vulnerabilities of Mobile Device Sensors Paula Delgado-Santos Giuseppe Stragapede Ruben Tolosana R. Guest F. Deravi R. Vera-Rodríguez PILM 111 55 0 18 Jun 2021
Interval Privacy: A Framework for Privacy-Preserving Data Collection Jie Ding Bangjun Ding 140 6 0 17 Jun 2021
Privacy Assessment of Federated Learning using Private Personalized Layers T. Jourdan A. Boutet Carole Frindel FedML 94 7 0 15 Jun 2021
Distributed Banach-Picard Iteration for Locally Contractive Maps Francisco Andrade Mário A. T. Figueiredo J. Xavier 93 2 0 31 Mar 2021
Active Privacy-utility Trade-off Against a Hypothesis Testing Adversary Ece Naz Erdemir Pier Luigi Dragotti Deniz Gunduz 107 9 0 16 Feb 2021
Impact of Data Processing on Fairness in Supervised Learning S. Khodadadian AmirEmad Ghassami Negar Kiyavash FaML 66 6 0 03 Feb 2021
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients Chris Cundy Rishi Desai Stefano Ermon OffRL 163 4 0 30 Dec 2020
Fundamental Limits of Obfuscation for Linear Gaussian Dynamical Systems: An Information-Theoretic Approach Song Fang Quanyan Zhu 59 4 0 29 Oct 2020
Non-Stochastic Private Function Evaluation F. Farokhi G. Nair 77 3 0 20 Oct 2020
Learning, compression, and leakage: Minimising classification error via meta-universal compression principles F. Rosas P. Mediano Michael C. Gastpar 62 11 0 14 Oct 2020
Data-driven Regularized Inference Privacy C. Wang Wee Peng Tay 115 3 0 10 Oct 2020
Privacy in Targeted Advertising: A Survey Imdad Ullah R. Boreli S. Kanhere 178 20 0 15 Sep 2020
Information Laundering for Model Privacy Xinran Wang Yu Xiang Jun Gao Jie Ding 49 24 0 13 Sep 2020
On Perfect Obfuscation: Local Information Geometry Analysis Behrooz Razeghi Flavio du Pin Calmon Deniz Gunduz Svyatoslav Voloshynovskiy 72 14 0 09 Sep 2020
Imitation Privacy Xun Xian Xinran Wang Mingyi Hong Jie Ding R. Ghanadan 89 3 0 30 Aug 2020
Robust Machine Learning via Privacy/Rate-Distortion Theory Ye Wang Shuchin Aeron Adnan Siraj Rakin T. Koike-Akino P. Moulin OOD 92 7 0 22 Jul 2020
No-Go Theorems for Data Privacy T. Studer 35 2 0 28 May 2020
Operationalizing the Legal Principle of Data Minimization for Personalization Asia J. Biega P. Potash Hal Daumé Fernando Diaz Michèle Finck AILaw 109 76 0 28 May 2020
Assisted Learning: A Framework for Multi-Organization Learning Xun Xian Xinran Wang Jie Ding R. Ghanadan FedML 90 1 0 01 Apr 2020