Data Poisoning against Differentially-Private Learners: Attacks and Defenses

23 March 2019

Papers citing "Data Poisoning against Differentially-Private Learners: Attacks and Defenses"

25 / 25 papers shown

Title
Crowding Out The Noise: Algorithmic Collective Action Under Differential Privacy Rushabh Solanki Meghana Bhange Ulrich Aïvodji Elliot Creager 29 0 0 09 May 2025
Game-Theoretic Defenses for Robust Conformal Prediction Against Adversarial Attacks in Medical Imaging Rui Luo Jie Bao Zhixin Zhou Chuangyin Dang MedIm AAML 37 5 0 07 Nov 2024
PureEBM: Universal Poison Purification via Mid-Run Dynamics of Energy-Based Models Omead Brandon Pooladzandi Jeffrey Q. Jiang Sunay Bhat Gregory Pottie AAML 31 0 0 28 May 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 25 16 0 02 Feb 2024
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective Xianghua Xie Chen Hu Hanchi Ren Jingjing Deng FedML AAML 29 19 0 27 Nov 2023
PrivImage: Differentially Private Synthetic Image Generation using Diffusion Models with Semantic-Aware Pretraining Kecen Li Chen Gong Zhixiang Li Yuzhong Zhao Xinwen Hou Tianhao Wang 27 10 0 19 Oct 2023
Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks Shijie Liu Andrew C. Cullen Paul Montague S. Erfani Benjamin I. P. Rubinstein AAML 20 3 0 15 Aug 2023
Universal Soldier: Using Universal Adversarial Perturbations for Detecting Backdoor Attacks Xiaoyun Xu Oguzhan Ersoy S. Picek AAML 21 2 0 01 Feb 2023
Backdoor Cleansing with Unlabeled Data Lu Pang Tao Sun Haibin Ling Chao Chen AAML 37 18 0 22 Nov 2022
A General Framework for Auditing Differentially Private Machine Learning Fred Lu Joseph Munoz Maya Fuchs Tyler LeBlond Elliott Zaresky-Williams Edward Raff Francis Ferraro Brian Testa FedML 16 35 0 16 Oct 2022
On the Robustness of Random Forest Against Untargeted Data Poisoning: An Ensemble-Based Approach M. Anisetti C. Ardagna Alessandro Balestrucci Nicola Bena Ernesto Damiani C. Yeun AAML OOD 24 10 0 28 Sep 2022
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks Chulin Xie Yunhui Long Pin-Yu Chen Qinbin Li Arash Nourian Sanmi Koyejo Bo Li FedML 35 13 0 08 Sep 2022
SNAP: Efficient Extraction of Private Properties with Poisoning Harsh Chaudhari John Abascal Alina Oprea Matthew Jagielski Florian Tramèr Jonathan R. Ullman MIACV 34 30 0 25 Aug 2022
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms Ehsan Hallaji R. Razavi-Far M. Saif AAML FedML 21 13 0 05 Jul 2022
Fine-grained Poisoning Attack to Local Differential Privacy Protocols for Mean and Variance Estimation Xiaoguang Li Ninghui Li Wenhai Sun Neil Zhenqiang Gong Hui Li AAML 56 15 0 24 May 2022
PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in Contrastive Learning Hongbin Liu Jinyuan Jia Neil Zhenqiang Gong 25 34 0 13 May 2022
ScaleSFL: A Sharding Solution for Blockchain-Based Federated Learning Evan W. R. Madill Ben Nguyen C. Leung Sara Rouhani 30 20 0 04 Apr 2022
Combining Differential Privacy and Byzantine Resilience in Distributed SGD R. Guerraoui Nirupam Gupta Rafael Pinot Sébastien Rouault John Stephan FedML 35 4 0 08 Oct 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 32 16 0 20 Sep 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 24 100 0 10 Aug 2021
A BIC-based Mixture Model Defense against Data Poisoning Attacks on Classifiers Xi Li David J. Miller Zhen Xiang G. Kesidis AAML 14 0 0 28 May 2021
Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release Liam H. Fowl Ping Yeh-Chiang Micah Goldblum Jonas Geiping Arpit Bansal W. Czaja Tom Goldstein 13 43 0 16 Feb 2021
Data Poisoning Attacks to Deep Learning Based Recommender Systems Hai Huang Jiaming Mu Neil Zhenqiang Gong Qi Li Bin Liu Mingwei Xu AAML 17 129 0 07 Jan 2021
Mitigating Sybil Attacks on Differential Privacy based Federated Learning Yupeng Jiang Yong Li Yipeng Zhou Xi Zheng FedML AAML 21 15 0 20 Oct 2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching Jonas Geiping Liam H. Fowl W. R. Huang W. Czaja Gavin Taylor Michael Moeller Tom Goldstein AAML 19 215 0 04 Sep 2020