Generative Poisoning Attack Method Against Neural Networks

3 March 2017

Yiran Chen

Papers citing "Generative Poisoning Attack Method Against Neural Networks"

29 / 29 papers shown

Title
On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning Yongyi Su Yushu Li Nanqing Liu Kui Jia Xulei Yang Chuan-Sheng Foo Xun Xu TTA AAML 56 0 0 07 Oct 2024
RLHFPoison: Reward Poisoning Attack for Reinforcement Learning with Human Feedback in Large Language Models Jiong Wang Junlin Wu Muhao Chen Yevgeniy Vorobeychik Chaowei Xiao AAML 21 12 0 16 Nov 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
Test-Time Poisoning Attacks Against Test-Time Adaptation Models Tianshuo Cong Xinlei He Yun Shen Yang Zhang AAML TTA 19 5 0 16 Aug 2023
A Blockchain-based Platform for Reliable Inference and Training of Large-Scale Models Sanghyeon Park Junmo Lee Soo-Mook Moon 38 1 0 06 May 2023
Mole Recruitment: Poisoning of Image Classifiers via Selective Batch Sampling Ethan Wisdom Tejas Gokhale Chaowei Xiao Yezhou Yang 18 0 0 30 Mar 2023
The Value of Out-of-Distribution Data Ashwin De Silva Rahul Ramesh Carey E. Priebe Pratik Chaudhari Joshua T. Vogelstein OODD 16 11 0 23 Aug 2022
Integrity Authentication in Tree Models Weijie Zhao Yingjie Lao Ping Li 54 5 0 30 May 2022
One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks Shutong Wu Sizhe Chen Cihang Xie X. Huang AAML 42 26 0 24 May 2022
Poisoning Attacks and Defenses on Artificial Intelligence: A Survey M. A. Ramírez Song-Kyoo Kim H. A. Hamadi Ernesto Damiani Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 11 37 0 21 Feb 2022
A Survey on Poisoning Attacks Against Supervised Machine Learning Wenjun Qiu AAML 20 9 0 05 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
De-Pois: An Attack-Agnostic Defense against Data Poisoning Attacks Jian Chen Xuxin Zhang Rui Zhang Chen Wang Ling Liu AAML 17 86 0 08 May 2021
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics J. Hayase Weihao Kong Raghav Somani Sewoong Oh AAML 19 149 0 22 Apr 2021
The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers? Antonio Emanuele Cinà Sebastiano Vascon Ambra Demontis Battista Biggio Fabio Roli Marcello Pelillo AAML 19 9 0 23 Mar 2021
Unlearnable Examples: Making Personal Data Unexploitable Hanxun Huang Xingjun Ma S. Erfani James Bailey Yisen Wang MIACV 136 190 0 13 Jan 2021
Being Single Has Benefits. Instance Poisoning to Deceive Malware Classifiers T. Shapira David Berend Ishai Rosenberg Yang Liu A. Shabtai Yuval Elovici AAML 11 4 0 30 Oct 2020
Bias Field Poses a Threat to DNN-based X-Ray Recognition Binyu Tian Qing-Wu Guo Felix Juefei Xu W. L. Chan Yupeng Cheng Xiaohong Li Xiaofei Xie Shengchao Qin AAML AI4CE 24 33 0 19 Sep 2020
Data Poisoning Attacks Against Federated Learning Systems Vale Tolpegin Stacey Truex Mehmet Emre Gursoy Ling Liu FedML 23 637 0 16 Jul 2020
Defending against GAN-based Deepfake Attacks via Transformation-aware Adversarial Faces Chaofei Yang Lei Ding Yiran Chen H. Li AAML 8 46 0 12 Jun 2020
Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic Zhen Xiang David J. Miller Hang Wang G. Kesidis AAML 20 9 0 18 Nov 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 22 18 0 27 Sep 2019
On Defending Against Label Flipping Attacks on Malware Detection Systems R. Taheri R. Javidan Mohammad Shojafar Zahra Pooranian A. Miri Mauro Conti AAML 11 88 0 13 Aug 2019
Poisoning Attacks with Generative Adversarial Nets Luis Muñoz-González Bjarne Pfitzner Matteo Russo Javier Carnerero-Cano Emil C. Lupu AAML 11 63 0 18 Jun 2019
Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks Felipe A. Mejia Paul Gamble Z. Hampel-Arias M. Lomnitz Nina Lopatina Lucas Tindall M. Barrios SILM 13 18 0 15 Jun 2019
Bypassing Backdoor Detection Algorithms in Deep Learning T. Tan Reza Shokri FedML AAML 17 149 0 31 May 2019
A new Backdoor Attack in CNNs by training set corruption without label poisoning Mauro Barni Kassem Kallas B. Tondi AAML 18 347 0 12 Feb 2019
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks Octavian Suciu R. Marginean Yigitcan Kaya Hal Daumé Tudor Dumitras AAML 14 282 0 19 Mar 2018
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Bo-wen Li Kimberly Lu D. Song AAML SILM 13 1,800 0 15 Dec 2017