MetaPoison: Practical General-purpose Clean-label Data Poisoning

1 April 2020

Papers citing "MetaPoison: Practical General-purpose Clean-label Data Poisoning"

46 / 46 papers shown

Title
SFIBA: Spatial-based Full-target Invisible Backdoor Attacks Yangxu Yin H. Chen Yudong Gao Peng Sun Zehan Li Wei Liu AAML 45 0 0 29 Apr 2025
Approaching the Harm of Gradient Attacks While Only Flipping Labels Abdessamad El-Kabid El-Mahdi El-Mhamdi AAML 34 0 0 28 Feb 2025
Timber! Poisoning Decision Trees Stefano Calzavara Lorenzo Cazzaro Massimo Vettori AAML 30 0 0 01 Oct 2024
On ADMM in Heterogeneous Federated Learning: Personalization, Robustness, and Fairness Shengkun Zhu Jinshan Zeng Sheng Wang Yuan Sun Xiaodong Li Yuan Yao Zhiyong Peng 52 0 0 23 Jul 2024
DeepiSign-G: Generic Watermark to Stamp Hidden DNN Parameters for Self-contained Tracking A. Abuadbba Nicholas Rhodes Kristen Moore Bushra Sabir Shuo Wang Yansong Gao AAML 35 2 0 01 Jul 2024
Machine Unlearning Fails to Remove Data Poisoning Attacks Martin Pawelczyk Jimmy Z. Di Yiwei Lu Gautam Kamath Ayush Sekhari Seth Neel AAML MU 62 8 0 25 Jun 2024
Noisy Neighbors: Efficient membership inference attacks against LLMs Filippo Galli Luca Melis Tommaso Cucinotta 54 7 0 24 Jun 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
Corrective Machine Unlearning Shashwat Goel Ameya Prabhu Philip Torr Ponnurangam Kumaraguru Amartya Sanyal OnRL 42 14 0 21 Feb 2024
Tailoring Adversarial Attacks on Deep Neural Networks for Targeted Class Manipulation Using DeepFool Algorithm S. M. Fazle J. Mondal Meem Arafat Manab Xi Xiao Sarfaraz Newaz AAML 29 0 0 18 Oct 2023
Make Text Unlearnable: Exploiting Effective Patterns to Protect Personal Data Xinzhe Li Ming Liu Shang Gao MU 37 8 0 02 Jul 2023
On the Exploitability of Instruction Tuning Manli Shu Jiong Wang Chen Zhu Jonas Geiping Chaowei Xiao Tom Goldstein SILM 41 92 0 28 Jun 2023
Poisoning Web-Scale Training Datasets is Practical Nicholas Carlini Matthew Jagielski Christopher A. Choquette-Choo Daniel Paleka Will Pearce Hyrum S. Anderson Andreas Terzis Kurt Thomas Florian Tramèr SILM 31 182 0 20 Feb 2023
TrojanPuzzle: Covertly Poisoning Code-Suggestion Models H. Aghakhani Wei Dai Andre Manoel Xavier Fernandes Anant Kharkar Christopher Kruegel Giovanni Vigna David Evans B. Zorn Robert Sim SILM 29 33 0 06 Jan 2023
Unlearnable Clusters: Towards Label-agnostic Unlearnable Examples Jiaming Zhang Xingjun Ma Qiaomin Yi Jitao Sang Yugang Jiang Yaowei Wang Changsheng Xu 21 24 0 31 Dec 2022
Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks Jimmy Z. Di Jack Douglas Jayadev Acharya Gautam Kamath Ayush Sekhari MU 32 44 0 21 Dec 2022
Rethinking Backdoor Data Poisoning Attacks in the Context of Semi-Supervised Learning Marissa Connor Vincent Emanuele SILM AAML 27 1 0 05 Dec 2022
Membership Inference Attacks Against Semantic Segmentation Models Tomás Chobola Dmitrii Usynin Georgios Kaissis MIACV 32 6 0 02 Dec 2022
Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning Yuxin Wen Jonas Geiping Liam H. Fowl Hossein Souri Ramalingam Chellappa Micah Goldblum Tom Goldstein AAML SILM FedML 30 9 0 17 Oct 2022
Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class Khoa D. Doan Yingjie Lao Ping Li 34 40 0 17 Oct 2022
Detecting Backdoors in Deep Text Classifiers Youyan Guo Jun Wang Trevor Cohn SILM 42 1 0 11 Oct 2022
Advancing Model Pruning via Bi-level Optimization Yihua Zhang Yuguang Yao Parikshit Ram Pu Zhao Tianlong Chen Min-Fong Hong Yanzhi Wang Sijia Liu 49 68 0 08 Oct 2022
Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks Tianwei Liu Yu Yang Baharan Mirzasoleiman AAML 39 27 0 14 Aug 2022
One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks Shutong Wu Sizhe Chen Cihang Xie X. Huang AAML 48 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
WaveFuzz: A Clean-Label Poisoning Attack to Protect Your Voice Yunjie Ge Qianqian Wang Jingfeng Zhang Juntao Zhou Yunzhu Zhang Chao Shen AAML 22 6 0 25 Mar 2022
Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation Zayd Hammoudeh Daniel Lowd TDI 24 28 0 25 Jan 2022
LoMar: A Local Defense Against Poisoning Attack on Federated Learning Xingyu Li Zhe Qu Shangqing Zhao Bo Tang Zhuo Lu Yao-Hong Liu AAML 41 92 0 08 Jan 2022
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 31 9 0 19 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 39 6 0 25 Nov 2021
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning Neil G. Marchant Benjamin I. P. Rubinstein Scott Alfeld MU AAML 28 69 0 17 Sep 2021
Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning Akshay Mehra B. Kailkhura Pin-Yu Chen Jihun Hamm AAML 30 22 0 08 Jul 2021
Adversarial Examples Make Strong Poisons Liam H. Fowl Micah Goldblum Ping Yeh-Chiang Jonas Geiping Wojtek Czaja Tom Goldstein SILM 32 132 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 31 124 0 16 Jun 2021
Disrupting Model Training with Adversarial Shortcuts Ivan Evtimov Ian Covert Aditya Kusupati Tadayoshi Kohno AAML 28 10 0 12 Jun 2021
Defending Against Backdoor Attacks in Natural Language Generation Xiaofei Sun Xiaoya Li Yuxian Meng Xiang Ao Fei Wu Jiwei Li Tianwei Zhang AAML SILM 31 47 0 03 Jun 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 24 43 0 16 Feb 2021
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 27 270 0 18 Dec 2020
How Robust are Randomized Smoothing based Defenses to Data Poisoning? Akshay Mehra B. Kailkhura Pin-Yu Chen Jihun Hamm OOD AAML 20 32 0 02 Dec 2020
Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff Eitan Borgnia Valeriia Cherepanova Liam H. Fowl Amin Ghiasi Jonas Geiping Micah Goldblum Tom Goldstein Arjun Gupta AAML 22 127 0 18 Nov 2020
Concealed Data Poisoning Attacks on NLP Models Eric Wallace Tony Zhao Shi Feng Sameer Singh SILM 19 18 0 23 Oct 2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching Jonas Geiping Liam H. Fowl Yifan Jiang W. Czaja Gavin Taylor Michael Moeller Tom Goldstein AAML 19 215 0 04 Sep 2020
Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review Yansong Gao Bao Gia Doan Zhi-Li Zhang Siqi Ma Jiliang Zhang Anmin Fu Surya Nepal Hyoungshick Kim AAML 36 220 0 21 Jul 2020
Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks Avi Schwarzschild Micah Goldblum Arjun Gupta John P. Dickerson Tom Goldstein AAML TDI 21 162 0 22 Jun 2020
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 110 717 0 13 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 398 11,700 0 09 Mar 2017