v1v2v3 (latest)

Exploiting Unintended Feature Leakage in Collaborative Learning

10 May 2018

Luca Melis

Congzheng Song

Emiliano De Cristofaro

Vitaly Shmatikov

FedML

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Papers citing "Exploiting Unintended Feature Leakage in Collaborative Learning"

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Title
GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep LearningACM Symposium on Applied Computing (SAC), 2020 Vasisht Duddu A. Boutet Virat Shejwalkar GNN 149 4 0 02 Oct 2020
Quantifying Privacy Leakage in Graph EmbeddingInternational Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous), 2020 Vasisht Duddu A. Boutet Virat Shejwalkar MIACV 179 144 0 02 Oct 2020
Oblivious Sampling Algorithms for Private Data Analysis Sajin Sasy O. Ohrimenko FedML 148 19 0 28 Sep 2020
An Extension of Fano's Inequality for Characterizing Model Susceptibility to Membership Inference Attacks Sumit Kumar Jha Susmit Jha Rickard Ewetz Sunny Raj Alvaro Velasquez L. Pullum A. Swami MIACV 121 8 0 17 Sep 2020
Federated Dynamic GNN with Secure Aggregation Meng Jiang Taeho Jung Ryan Karl Tong Zhao FedML 163 33 0 15 Sep 2020
SAPAG: A Self-Adaptive Privacy Attack From Gradients Yijue Wang Jieren Deng Danyi Guo Chenghong Wang Xianrui Meng Hang Liu Caiwen Ding Sanguthevar Rajasekaran 112 39 0 14 Sep 2020
Federated Model Distillation with Noise-Free Differential PrivacyInternational Joint Conference on Artificial Intelligence (IJCAI), 2020 Lichao Sun Lingjuan Lyu FedML 199 118 0 11 Sep 2020
Privacy Analysis of Deep Learning in the Wild: Membership Inference Attacks against Transfer Learning Yang Zou Zhikun Zhang Michael Backes Yang Zhang MIACV 94 33 0 10 Sep 2020
Attribute Privacy: Framework and MechanismsConference on Fairness, Accountability and Transparency (FAccT), 2020 Wanrong Zhang O. Ohrimenko Rachel Cummings 177 39 0 08 Sep 2020
Local and Central Differential Privacy for Robustness and Privacy in Federated LearningNetwork and Distributed System Security Symposium (NDSS), 2020 Mohammad Naseri Jamie Hayes Emiliano De Cristofaro FedML 242 188 0 08 Sep 2020
A Comprehensive Analysis of Information Leakage in Deep Transfer Learning Cen Chen Bingzhe Wu Minghui Qiu Li Wang Jun Zhou PILM 75 12 0 04 Sep 2020
Sampling Attacks: Amplification of Membership Inference Attacks by Repeated Queries Shadi Rahimian Tribhuvanesh Orekondy Mario Fritz MIACV 79 36 0 01 Sep 2020
POSEIDON: Privacy-Preserving Federated Neural Network LearningNetwork and Distributed System Security Symposium (NDSS), 2020 Sinem Sav Apostolos Pyrgelis J. Troncoso-Pastoriza D. Froelicher Jean-Philippe Bossuat João Sá Sousa Jean-Pierre Hubaux FedML 194 168 0 01 Sep 2020
GRAFFL: Gradient-free Federated Learning of a Bayesian Generative Model S. Hahn Junghye Lee FedML 109 2 0 29 Aug 2020
Precision Health Data: Requirements, Challenges and Existing Techniques for Data Security and Privacy Chandra Thapa S. Çamtepe 129 257 0 24 Aug 2020
Addressing Class Imbalance in Federated Learning Lixu Wang Shichao Xu Tianlin Li Qi Zhu FedML 190 20 0 14 Aug 2020
Privacy Preserving Vertical Federated Learning for Tree-based Models Yuncheng Wu Shaofeng Cai Xiaokui Xiao Gang Chen Beng Chin Ooi FedML 165 243 0 14 Aug 2020
Towards Plausible Differentially Private ADMM Based Distributed Machine LearningInternational Conference on Information and Knowledge Management (CIKM), 2020 Jiahao Ding Jingyi Wang Guannan Liang J. Bi Miao Pan 179 12 0 11 Aug 2020
Improving on-device speaker verification using federated learning with privacyInterspeech (Interspeech), 2020 Filip Granqvist M. Seigel Rogier van Dalen Áine Cahill Stephen Shum Matthias Paulik FedML 147 60 0 06 Aug 2020
Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and ApplicationsProceedings of the IEEE (Proc. IEEE), 2020 Jihong Park S. Samarakoon Anis Elgabli Joongheon Kim M. Bennis Seong-Lyun Kim Mérouane Debbah 254 174 0 06 Aug 2020
Learner's Dilemma: IoT Devices Training Strategies in Collaborative Deep LearningWorld Forum on Internet of Things (WF-IoT), 2020 Deepti Gupta O. Kayode Smriti Bhatt Maanak Gupta A. Tosun 87 25 0 30 Jul 2020
Privacy-preserving Voice Analysis via Disentangled Representations Ranya Aloufi Hamed Haddadi David E. Boyle DRL 272 62 0 29 Jul 2020
Efficient Sparse Secure Aggregation for Federated Learning C. Béguier M. Andreux Eric W. Tramel FedML 129 19 0 29 Jul 2020
FedML: A Research Library and Benchmark for Federated Machine Learning Chaoyang He Songze Li Jinhyun So Xiao Zeng Mi Zhang ... Yang Liu Ramesh Raskar Qiang Yang M. Annavaram Salman Avestimehr FedML 480 647 0 27 Jul 2020
Anonymizing Machine Learning Models Abigail Goldsteen Gilad Ezov Ron Shmelkin Micha Moffie Ariel Farkash MIACV 139 7 0 26 Jul 2020
Privacy-preserving Artificial Intelligence Techniques in Biomedicine Reihaneh Torkzadehmahani Reza Nasirigerdeh David B. Blumenthal T. Kacprowski M. List ... Harald H. H. W. Schmidt A. Schwalber Christof Tschohl Andrea Wohner Jan Baumbach 257 78 0 22 Jul 2020
Improving Deep Learning with Differential Privacy using Gradient Encoding and Denoising Milad Nasr Reza Shokri Amir Houmansadr 115 46 0 22 Jul 2020
IBM Federated Learning: an Enterprise Framework White Paper V0.1 Heiko Ludwig Nathalie Baracaldo Gegi Thomas Yi Zhou Ali Anwar ... Sean Laguna Mikhail Yurochkin Mayank Agarwal Ebube Chuba Annie Abay FedML 327 181 0 22 Jul 2020
Data Poisoning Attacks Against Federated Learning SystemsEuropean Symposium on Research in Computer Security (ESORICS), 2020 Vale Tolpegin Stacey Truex Mehmet Emre Gursoy Ling Liu FedML 228 808 0 16 Jul 2020
Less is More: A privacy-respecting Android malware classifier using Federated LearningProceedings on Privacy Enhancing Technologies (PoPETs), 2020 Rafa Gálvez Veelasha Moonsamy Claudia Díaz FedML 138 36 0 16 Jul 2020
A Survey of Privacy Attacks in Machine LearningACM Computing Surveys (ACM CSUR), 2020 M. Rigaki Sebastian Garcia PILM AAML 243 279 0 15 Jul 2020
FedBoosting: Federated Learning with Gradient Protected Boosting for Text RecognitionNeurocomputing (Neurocomputing), 2020 Hanchi Ren Jingjing Deng Xianghua Xie Xiaoke Ma Yi-Cheng Wang FedML 221 14 0 14 Jul 2020
PrivColl: Practical Privacy-Preserving Collaborative Machine LearningEuropean Symposium on Research in Computer Security (ESORICS), 2020 Yanjun Zhang Guangdong Bai Xue Li Caitlin I. Curtis Chong Chen R. Ko FedML 115 37 0 14 Jul 2020
Quality Inference in Federated Learning with Secure AggregationIEEE Transactions on Big Data (IEEE Trans. Big Data), 2020 Balázs Pejó G. Biczók FedML 302 26 0 13 Jul 2020
Federated Learning of User Authentication Models H. Hosseini Sungrack Yun Hyunsin Park Christos Louizos Joseph B. Soriaga Max Welling FedML 104 14 0 09 Jul 2020
BlockFLow: An Accountable and Privacy-Preserving Solution for Federated Learning Vaikkunth Mugunthan Ravi Rahman Lalana Kagal FedML 174 44 0 08 Jul 2020
Privacy Threats Against Federated Matrix Factorization Dashan Gao Ben Tan Ce Ju V. Zheng Qiang Yang 130 14 0 03 Jul 2020
Rotation-Equivariant Neural Networks for Privacy Protection Hao Zhang Yiting Chen Haotian Ma Feng He Qihan Ren Liyao Xiang Jie Shi Quanshi Zhang 79 4 0 21 Jun 2020
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks Lixin Fan Kam Woh Ng Ce Ju Tianyu Zhang Chang Liu Chee Seng Chan Qiang Yang MIACV 123 66 0 20 Jun 2020
Topology-aware Differential Privacy for Decentralized Image Classification Shangwei Guo Tianwei Zhang Guowen Xu Hanzhou Yu Tao Xiang Yang Liu 184 18 0 14 Jun 2020
Understanding Unintended Memorization in Federated Learning Om Thakkar Swaroop Indra Ramaswamy Rajiv Mathews Franccoise Beaufays FedML 178 48 0 12 Jun 2020
An Accurate, Scalable and Verifiable Protocol for Federated Differentially Private AveragingMachine-mediated learning (ML), 2020 C. Sabater A. Bellet J. Ramon FedML 232 30 0 12 Jun 2020
Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data Chengxu Yang Qipeng Wang Mengwei Xu Shangguang Wang Kaigui Bian Yunxin Liu Xuanzhe Liu 138 24 0 12 Jun 2020
Scalable Privacy-Preserving Distributed Learning D. Froelicher J. Troncoso-Pastoriza Apostolos Pyrgelis Sinem Sav João Sá Sousa Jean-Philippe Bossuat Jean-Pierre Hubaux FedML 194 73 0 19 May 2020
Fair Inputs and Fair Outputs: The Incompatibility of Fairness in Privacy and Accuracy Bashir Rastegarpanah M. Crovella Krishna P. Gummadi FaML 216 9 0 19 May 2020
An Overview of Privacy in Machine Learning Emiliano De Cristofaro SILM 157 97 0 18 May 2020
Efficient Federated Learning over Multiple Access Channel with Differential Privacy Constraints Amir Sonee Stefano Rini 122 17 0 15 May 2020
Defending Model Inversion and Membership Inference Attacks via Prediction Purification Ziqi Yang Bin Shao Bohan Xuan E. Chang Fan Zhang AAML 138 79 0 08 May 2020
When Machine Unlearning Jeopardizes PrivacyConference on Computer and Communications Security (CCS), 2020 Min Chen Zhikun Zhang Tianhao Wang Michael Backes Mathias Humbert Yang Zhang MIACV 224 279 0 05 May 2020
Differentially Private Federated Learning with Laplacian SmoothingApplied and Computational Harmonic Analysis (ACHA), 2020 Zhicong Liang Bao Wang Quanquan Gu Stanley Osher Xingtai Lv FedML 132 11 0 01 May 2020