An Overview of Privacy in Machine Learning

18 May 2020

Papers citing "An Overview of Privacy in Machine Learning"

16 / 16 papers shown

Title
On the Privacy-Preserving Properties of Spiking Neural Networks with Unique Surrogate Gradients and Quantization Levels Ayana Moshruba Shay Snyder Hamed Poursiami Maryam Parsa AAML 71 2 0 25 Feb 2025
Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study Ayana Moshruba Ihsen Alouani Maryam Parsa AAML 54 3 0 24 Feb 2025
SoK: Unintended Interactions among Machine Learning Defenses and Risks Vasisht Duddu S. Szyller Nadarajah Asokan AAML 47 2 0 07 Dec 2023
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources Suraj Rajendran Weishen Pan M. Sabuncu Yong Chen Jiayu Zhou Fei Wang 57 14 0 10 May 2023
On the Alignment of Group Fairness with Attribute Privacy Jan Aalmoes Vasisht Duddu A. Boutet 43 2 0 18 Nov 2022
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity Faisal Hamman Jiahao Chen Sanghamitra Dutta 25 9 0 03 Nov 2022
Exploiting Fairness to Enhance Sensitive Attributes Reconstruction Julien Ferry Ulrich Aïvodji Sébastien Gambs Marie-José Huguet Mohamed Siala AAML 37 14 0 02 Sep 2022
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 104 196 0 12 Jul 2021
Survey: Leakage and Privacy at Inference Time Marija Jegorova Chaitanya Kaul Charlie Mayor Alison Q. OÑeil Alexander Weir Roderick Murray-Smith Sotirios A. Tsaftaris PILM MIACV 23 71 0 04 Jul 2021
Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs Mohammad Malekzadeh Anastasia Borovykh Deniz Gündüz MIACV 24 42 0 25 May 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 35 412 0 14 Mar 2021
PRICURE: Privacy-Preserving Collaborative Inference in a Multi-Party Setting Ismat Jarin Birhanu Eshete 26 18 0 19 Feb 2021
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models Yugeng Liu Rui Wen Xinlei He A. Salem Zhikun Zhang Michael Backes Emiliano De Cristofaro Mario Fritz Yang Zhang AAML 17 125 0 04 Feb 2021
R-GAP: Recursive Gradient Attack on Privacy Junyi Zhu Matthew Blaschko FedML 14 132 0 15 Oct 2020
Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins? Jeremy Georges-Filteau Elisa Cirillo SyDa AI4CE 36 17 0 27 May 2020
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 114 395 0 08 Jun 2018