Subpopulation Data Poisoning Attacks

24 June 2020

Matthew Jagielski

Giorgio Severi

Niklas Pousette Harger

Papers citing "Subpopulation Data Poisoning Attacks"

22 / 22 papers shown

Title
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning Shihua Sun Shridatt Sugrim Angelos Stavrou Haining Wang AAML 63 1 0 13 Jul 2024
TrustGuard: GNN-based Robust and Explainable Trust Evaluation with Dynamicity Support Jie Wang Zheng Yan Jiahe Lan Elisa Bertino Witold Pedrycz 25 11 0 23 Jun 2023
Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition Luke E. Richards Edward Raff Cynthia Matuszek AAML 16 2 0 17 Feb 2023
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data Minghong Fang Jia-Wei Liu Michinari Momma Yi Sun 27 4 0 13 Dec 2022
On Optimal Learning Under Targeted Data Poisoning Steve Hanneke Amin Karbasi Mohammad Mahmoody Idan Mehalel Shay Moran AAML FedML 30 7 0 06 Oct 2022
Data Isotopes for Data Provenance in DNNs Emily Wenger Xiuyu Li Ben Y. Zhao Vitaly Shmatikov 20 12 0 29 Aug 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
PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in Contrastive Learning Hongbin Liu Jinyuan Jia Neil Zhenqiang Gong 25 34 0 13 May 2022
Subverting Fair Image Search with Generative Adversarial Perturbations A. Ghosh Matthew Jagielski Chris L. Wilson 22 7 0 05 May 2022
Backdoor Attacks in Federated Learning by Rare Embeddings and Gradient Ensembling Kiyoon Yoo Nojun Kwak SILM AAML FedML 19 19 0 29 Apr 2022
Machine Learning Security against Data Poisoning: Are We There Yet? Antonio Emanuele Cinà Kathrin Grosse Ambra Demontis Battista Biggio Fabio Roli Marcello Pelillo AAML 24 35 0 12 Apr 2022
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning A. Mondal Harpreet Virk Debayan Gupta 34 15 0 06 Feb 2022
Securing Federated Sensitive Topic Classification against Poisoning Attacks Tianyue Chu Álvaro García-Recuero Costas Iordanou Georgios Smaragdakis Nikolaos Laoutaris 38 9 0 31 Jan 2022
Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation Zayd Hammoudeh Daniel Lowd TDI 21 28 0 25 Jan 2022
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
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
Data Appraisal Without Data Sharing Mimee Xu L. V. D. van der Maaten Awni Y. Hannun TDI 36 6 0 11 Dec 2020
MalFox: Camouflaged Adversarial Malware Example Generation Based on Conv-GANs Against Black-Box Detectors Fangtian Zhong Xiuzhen Cheng Dongxiao Yu Bei Gong Shuaiwen Leon Song Jiguo Yu AAML 43 29 0 03 Nov 2020
Concealed Data Poisoning Attacks on NLP Models Eric Wallace Tony Zhao Shi Feng Sameer Singh SILM 16 18 0 23 Oct 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
Blind Backdoors in Deep Learning Models Eugene Bagdasaryan Vitaly Shmatikov AAML FedML SILM 46 298 0 08 May 2020
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 297 10,220 0 16 Nov 2016