Unlearnable Examples: Making Personal Data Unexploitable

13 January 2021

Papers citing "Unlearnable Examples: Making Personal Data Unexploitable"

37 / 137 papers shown

Title
Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors Sizhe Chen Geng Yuan Xinwen Cheng Yifan Gong Minghai Qin Yanzhi Wang X. Huang AAML 28 20 0 22 Nov 2022
UPTON: Preventing Authorship Leakage from Public Text Release via Data Poisoning Ziyao Wang Thai Le Dongwon Lee 33 1 0 17 Nov 2022
Generative Poisoning Using Random Discriminators Dirren van Vlijmen A. Kolmus Zhuoran Liu Zhengyu Zhao Martha Larson 23 2 0 02 Nov 2022
Transferable Unlearnable Examples J. Ren Han Xu Yuxuan Wan Xingjun Ma Lichao Sun Jiliang Tang 36 36 0 18 Oct 2022
Data Isotopes for Data Provenance in DNNs Emily Wenger Xiuyu Li Ben Y. Zhao Vitaly Shmatikov 20 12 0 29 Aug 2022
Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection Simin Li Huangxinxin Xu Jiakai Wang Aishan Liu Fazhi He Xianglong Liu Dacheng Tao AAML 21 5 0 23 Aug 2022
Autoregressive Perturbations for Data Poisoning Pedro Sandoval-Segura Vasu Singla Jonas Geiping Micah Goldblum Tom Goldstein David Jacobs AAML 25 40 0 08 Jun 2022
One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks Shutong Wu Sizhe Chen Cihang Xie X. Huang AAML 45 27 0 24 May 2022
Indiscriminate Data Poisoning Attacks on Neural Networks Yiwei Lu Gautam Kamath Yaoliang Yu AAML 43 24 0 19 Apr 2022
Poisons that are learned faster are more effective Pedro Sandoval-Segura Vasu Singla Liam H. Fowl Jonas Geiping Micah Goldblum David Jacobs Tom Goldstein 6 17 0 19 Apr 2022
Robust Unlearnable Examples: Protecting Data Against Adversarial Learning Shaopeng Fu Fengxiang He Yang Liu Li Shen Dacheng Tao 19 24 0 28 Mar 2022
Deep Learning Serves Traffic Safety Analysis: A Forward-looking Review Abolfazl Razi Xiwen Chen Huayu Li Hao Wang Brendan J. Russo Yan Chen Hongbin Yu 27 39 0 07 Mar 2022
Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations Tao Guo Song Guo Jiewei Zhang Wenchao Xu Junxiao Wang MU 27 17 0 27 Feb 2022
Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning Hao He Kaiwen Zha Dina Katabi AAML 34 32 0 22 Feb 2022
Learnability Lock: Authorized Learnability Control Through Adversarial Invertible Transformations Weiqi Peng Jinghui Chen AAML 16 5 0 03 Feb 2022
Can Adversarial Training Be Manipulated By Non-Robust Features? Lue Tao Lei Feng Hongxin Wei Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 81 16 0 31 Jan 2022
Certifying Model Accuracy under Distribution Shifts Aounon Kumar Alexander Levine Tom Goldstein S. Feizi OOD 27 7 0 28 Jan 2022
Execute Order 66: Targeted Data Poisoning for Reinforcement Learning Harrison Foley Liam H. Fowl Tom Goldstein Gavin Taylor AAML 17 9 0 03 Jan 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 194 345 0 15 Dec 2021
Amicable Aid: Perturbing Images to Improve Classification Performance Juyeop Kim Jun-Ho Choi Soobeom Jang Jong-Seok Lee AAML 13 2 0 09 Dec 2021
SoK: Anti-Facial Recognition Technology Emily Wenger Shawn Shan Haitao Zheng Ben Y. Zhao PICV 32 13 0 08 Dec 2021
Going Grayscale: The Road to Understanding and Improving Unlearnable Examples Zhuoran Liu Zhengyu Zhao A. Kolmus Tijn Berns Twan van Laarhoven Tom Heskes Martha Larson AAML 37 6 0 25 Nov 2021
Fooling Adversarial Training with Inducing Noise Zhirui Wang Yifei Wang Yisen Wang 17 14 0 19 Nov 2021
Fast Yet Effective Machine Unlearning Ayush K Tarun Vikram S Chundawat Murari Mandal Mohan S. Kankanhalli MU 31 171 0 17 Nov 2021
Availability Attacks Create Shortcuts Da Yu Huishuai Zhang Wei Chen Jian Yin Tie-Yan Liu AAML 31 57 0 01 Nov 2021
Robust Contrastive Learning Using Negative Samples with Diminished Semantics Songwei Ge Shlok Kumar Mishra Haohan Wang Chun-Liang Li David Jacobs SSL 24 71 0 27 Oct 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
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
Adversarial Examples Make Strong Poisons Liam H. Fowl Micah Goldblum Ping Yeh-Chiang Jonas Geiping Wojtek Czaja Tom Goldstein SILM 23 132 0 21 Jun 2021
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch Hossein Souri Liam H. Fowl Ramalingam Chellappa Micah Goldblum Tom Goldstein SILM 31 123 0 16 Jun 2021
Disrupting Model Training with Adversarial Shortcuts Ivan Evtimov Ian Covert Aditya Kusupati Tadayoshi Kohno AAML 20 10 0 12 Jun 2021
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training Lue Tao Lei Feng Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 31 71 0 09 Feb 2021
With False Friends Like These, Who Can Notice Mistakes? Lue Tao Lei Feng Jinfeng Yi Songcan Chen AAML 13 5 0 29 Dec 2020
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses Micah Goldblum Dimitris Tsipras Chulin Xie Xinyun Chen Avi Schwarzschild D. Song A. Madry Bo-wen Li Tom Goldstein SILM 18 270 0 18 Dec 2020
Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles Ranjie Duan Xingjun Ma Yisen Wang James Bailey •. A. K. Qin Yun Yang AAML 167 224 0 08 Mar 2020
Clean-Label Backdoor Attacks on Video Recognition Models Shihao Zhao Xingjun Ma Xiang Zheng James Bailey Jingjing Chen Yu-Gang Jiang AAML 196 274 0 06 Mar 2020
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,837 0 08 Jul 2016