When Machine Unlearning Jeopardizes Privacy

5 May 2020

Michael Backes

Papers citing "When Machine Unlearning Jeopardizes Privacy"

42 / 42 papers shown

Title
CRFU: Compressive Representation Forgetting Against Privacy Leakage on Machine Unlearning Weiqi Wang Chenhan Zhang Zhiyi Tian Shushu Liu Shui Yu MU 42 0 0 27 Feb 2025
SCU: An Efficient Machine Unlearning Scheme for Deep Learning Enabled Semantic Communications Weiqi Wang Zhiyi Tian Chenhan Zhang Shui Yu MU 70 1 0 27 Feb 2025
Privacy Ripple Effects from Adding or Removing Personal Information in Language Model Training Jaydeep Borkar Matthew Jagielski Katherine Lee Niloofar Mireshghallah David A. Smith Christopher A. Choquette-Choo PILM 78 1 0 24 Feb 2025
Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models Vinith M. Suriyakumar Rohan Alur Ayush Sekhari Manish Raghavan Ashia C. Wilson 53 2 0 10 Oct 2024
Alternate Preference Optimization for Unlearning Factual Knowledge in Large Language Models Anmol Mekala Vineeth Dorna Shreya Dubey Abhishek Lalwani David Koleczek Mukund Rungta Sadid Hasan Elita Lobo KELM MU 36 1 0 20 Sep 2024
RLCP: A Reinforcement Learning-based Copyright Protection Method for Text-to-Image Diffusion Model Zhuan Shi Jing Yan Xiaoli Tang Lingjuan Lyu Boi Faltings 34 1 0 29 Aug 2024
Towards Certified Unlearning for Deep Neural Networks Binchi Zhang Yushun Dong Tianhao Wang Jundong Li MU 57 7 0 01 Aug 2024
Machine Unlearning Fails to Remove Data Poisoning Attacks Martin Pawelczyk Jimmy Z. Di Yiwei Lu Gautam Kamath Ayush Sekhari Seth Neel AAML MU 54 8 0 25 Jun 2024
Adversarial Machine Unlearning Zonglin Di Sixie Yu Yevgeniy Vorobeychik Yang Liu 33 2 0 11 Jun 2024
Privacy-Preserving Debiasing using Data Augmentation and Machine Unlearning Zhixin Pan Emma Andrews Laura Chang Prabhat Mishra MU 38 1 0 19 Apr 2024
Privacy-Preserving Federated Unlearning with Certified Client Removal Ziyao Liu Huanyi Ye Yu Jiang Jiyuan Shen Jiale Guo Ivan Tjuawinata Kwok-Yan Lam MU 27 5 0 15 Apr 2024
Threats, Attacks, and Defenses in Machine Unlearning: A Survey Ziyao Liu Huanyi Ye Chen Chen Yongsen Zheng K. Lam AAML MU 29 28 0 20 Mar 2024
Efficient Knowledge Deletion from Trained Models through Layer-wise Partial Machine Unlearning Vinay Chakravarthi Gogineni E. Nadimi MU 29 1 0 12 Mar 2024
Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language Models Wenqi Jiang Marco Zeller R. Waleffe Torsten Hoefler Gustavo Alonso 47 16 0 15 Oct 2023
Machine Unlearning Methodology base on Stochastic Teacher Network Xulong Zhang Jianzong Wang Ning Cheng Yifu Sun Chuanyao Zhang Jing Xiao MU 13 4 0 28 Aug 2023
Membership Inference Attack for Beluga Whales Discrimination Voncarlos Marcelo Araújo Sébastien Gambs Clément Chion Robert Michaud L. Schneider H. Lautraite 19 2 0 28 Feb 2023
Towards Unbounded Machine Unlearning M. Kurmanji Peter Triantafillou Jamie Hayes Eleni Triantafillou MU 17 122 0 20 Feb 2023
Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning Xiangrong Zhu Guang-pu Li Wei Hu MU FedML 20 46 0 04 Feb 2023
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice Giovanni Apruzzese Hyrum S. Anderson Savino Dambra D. Freeman Fabio Pierazzi Kevin A. Roundy AAML 31 75 0 29 Dec 2022
Similarity Distribution based Membership Inference Attack on Person Re-identification Junyao Gao Xinyang Jiang Huishuai Zhang Yifan Yang Shuguang Dou Dongsheng Li Duoqian Miao Cheng Deng Cairong Zhao 23 7 0 29 Nov 2022
Forget Unlearning: Towards True Data-Deletion in Machine Learning R. Chourasia Neil Shah MU 13 39 0 17 Oct 2022
M^4I: Multi-modal Models Membership Inference Pingyi Hu Zihan Wang Ruoxi Sun Hu Wang Minhui Xue 37 26 0 15 Sep 2022
On the Privacy Risks of Cell-Based NAS Architectures Haiping Huang Zhikun Zhang Yun Shen Michael Backes Qi Li Yang Zhang 22 7 0 04 Sep 2022
VeriFi: Towards Verifiable Federated Unlearning Xiangshan Gao Xingjun Ma Jingyi Wang Youcheng Sun Bo Li S. Ji Peng Cheng Jiming Chen MU 65 46 0 25 May 2022
How to Combine Membership-Inference Attacks on Multiple Updated Models Matthew Jagielski Stanley Wu Alina Oprea Jonathan R. Ullman Roxana Geambasu 21 10 0 12 May 2022
Deep Learning for Computational Cytology: A Survey Hao Jiang Yanning Zhou Yi-Mou Lin R. Chan Jiangshu Liu Hao Chen 19 75 0 10 Feb 2022
Deletion Inference, Reconstruction, and Compliance in Machine (Un)Learning Ji Gao Sanjam Garg Mohammad Mahmoody Prashant Nalini Vasudevan MIACV AAML 19 22 0 07 Feb 2022
Towards Adversarial Evaluations for Inexact Machine Unlearning Shashwat Goel Ameya Prabhu Amartya Sanyal Ser-Nam Lim Philip H. S. Torr Ponnurangam Kumaraguru AAML ELM MU 26 45 0 17 Jan 2022
Fast Yet Effective Machine Unlearning Ayush K Tarun Vikram S Chundawat Murari Mandal Mohan S. Kankanhalli MU 31 168 0 17 Nov 2021
Property Inference Attacks Against GANs Junhao Zhou Yufei Chen Chao Shen Yang Zhang AAML MIACV 28 52 0 15 Nov 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 30 16 0 20 Sep 2021
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning Neil G. Marchant Benjamin I. P. Rubinstein Scott Alfeld MU AAML 20 69 0 17 Sep 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 17 71 0 04 Jul 2021
SoK: Privacy-Preserving Collaborative Tree-based Model Learning Sylvain Chatel Apostolos Pyrgelis J. Troncoso-Pastoriza Jean-Pierre Hubaux 15 14 0 16 Mar 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 30 412 0 14 Mar 2021
Remember What You Want to Forget: Algorithms for Machine Unlearning Ayush Sekhari Jayadev Acharya Gautam Kamath A. Suresh FedML MU 26 283 0 04 Mar 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning Xinlei He Yang Zhang 11 51 0 08 Feb 2021
A privacy-preserving approach to streaming eye-tracking data Brendan David-John D. Hosfelt Kevin R. B. Butler Eakta Jain 27 70 0 02 Feb 2021
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning Seth Neel Aaron Roth Saeed Sharifi-Malvajerdi MU 6 249 0 06 Jul 2020
Towards Probabilistic Verification of Machine Unlearning David M. Sommer Liwei Song Sameer Wagh Prateek Mittal AAML 11 71 0 09 Mar 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers Thomas Baumhauer Pascal Schöttle Matthias Zeppelzauer MU 102 130 0 07 Feb 2020
Model-Reuse Attacks on Deep Learning Systems Yujie Ji Xinyang Zhang S. Ji Xiapu Luo Ting Wang SILM AAML 134 186 0 02 Dec 2018