Exacerbating Algorithmic Bias through Fairness Attacks

16 December 2020

Papers citing "Exacerbating Algorithmic Bias through Fairness Attacks"

44 / 44 papers shown

Title
FairSAM: Fair Classification on Corrupted Data Through Sharpness-Aware Minimization Yucong Dai Jie Ji Xiaolong Ma Yongkai Wu 51 0 0 29 Mar 2025
Do Fairness Interventions Come at the Cost of Privacy: Evaluations for Binary Classifiers Huan Tian Guangsheng Zhang Bo Liu Tianqing Zhu Ming Ding Wanlei Zhou 53 0 0 08 Mar 2025
BadFair: Backdoored Fairness Attacks with Group-conditioned Triggers Jiaqi Xue Qian Lou Mengxin Zheng 31 1 0 23 Oct 2024
PFAttack: Stealthy Attack Bypassing Group Fairness in Federated Learning Jiashi Gao Ziwei Wang Xiangyu Zhao Xin Yao Xuetao Wei 25 0 0 09 Oct 2024
EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning Syed Irfan Ali Meerza Jian-Dong Liu 35 2 0 02 Oct 2024
A Catalog of Fairness-Aware Practices in Machine Learning Engineering Gianmario Voria Giulia Sellitto Carmine Ferrara Francesco Abate A. Lucia F. Ferrucci Gemma Catolino Fabio Palomba FaML 36 3 0 29 Aug 2024
LayerMatch: Do Pseudo-labels Benefit All Layers? Chaoqi Liang Guanglei Yang Lifeng Qiao Zitong Huang Hongliang Yan Yunchao Wei W. Zuo 46 0 0 20 Jun 2024
Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections Zihan Luo Hong Huang Yongkang Zhou Jiping Zhang Nuo Chen 37 1 0 05 Jun 2024
AI Risk Management Should Incorporate Both Safety and Security Xiangyu Qi Yangsibo Huang Yi Zeng Edoardo Debenedetti Jonas Geiping ... Chaowei Xiao Bo-wen Li Dawn Song Peter Henderson Prateek Mittal AAML 48 10 0 29 May 2024
Safety in Graph Machine Learning: Threats and Safeguards Song Wang Yushun Dong Binchi Zhang Zihan Chen Xingbo Fu Yinhan He Cong Shen Chuxu Zhang Nitesh V. Chawla Jundong Li 45 7 0 17 May 2024
Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models Anshuman Chhabra Bo Li Jian Chen Prasant Mohapatra Hongfu Liu TDI 34 0 0 06 May 2024
Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An Adversarial Perspective Xinjian Luo Yangfan Jiang Fei Wei Yuncheng Wu Xiaokui Xiao Beng Chin Ooi DiffM 38 4 0 28 Feb 2024
The Effect of Data Poisoning on Counterfactual Explanations André Artelt Shubham Sharma Freddy Lecue Barbara Hammer 18 1 0 13 Feb 2024
TrojFair: Trojan Fairness Attacks Meng Zheng Jiaqi Xue Yi Sheng Lei Yang Qian Lou Lei Jiang 10 3 0 16 Dec 2023
SoK: Unintended Interactions among Machine Learning Defenses and Risks Vasisht Duddu S. Szyller Nadarajah Asokan AAML 47 2 0 07 Dec 2023
Survey on AI Ethics: A Socio-technical Perspective Dave Mbiazi Meghana Bhange Maryam Babaei Ivaxi Sheth Patrik Joslin Kenfack 23 4 0 28 Nov 2023
Deceptive Fairness Attacks on Graphs via Meta Learning Jian Kang Yinglong Xia Ross Maciejewski Jiebo Luo Hanghang Tong 34 4 0 24 Oct 2023
Adversarial Attacks on Fairness of Graph Neural Networks Binchi Zhang Yushun Dong Chen Chen Yada Zhu Minnan Luo Jundong Li 38 3 0 20 Oct 2023
Towards Poisoning Fair Representations Tianci Liu Haoyu Wang Feijie Wu Hengtong Zhang Pan Li Lu Su Jing Gao AAML 30 2 0 28 Sep 2023
Adversarial attacks and defenses in explainable artificial intelligence: A survey Hubert Baniecki P. Biecek AAML 42 63 0 06 Jun 2023
Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures Eugenia Iofinova Alexandra Peste Dan Alistarh 23 9 0 25 Apr 2023
To be Robust and to be Fair: Aligning Fairness with Robustness Junyi Chai Xiaoqian Wang 47 2 0 31 Mar 2023
Improving Fair Training under Correlation Shifts Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 27 17 0 05 Feb 2023
Threats, Vulnerabilities, and Controls of Machine Learning Based Systems: A Survey and Taxonomy Yusuke Kawamoto Kazumasa Miyake K. Konishi Y. Oiwa 21 4 0 18 Jan 2023
A Survey on Preserving Fairness Guarantees in Changing Environments Ainhize Barrainkua Paula Gordaliza Jose A. Lozano Novi Quadrianto FaML 27 3 0 14 Nov 2022
Fairness-aware Regression Robust to Adversarial Attacks Yulu Jin Lifeng Lai FaML OOD 18 4 0 04 Nov 2022
Robust Fair Clustering: A Novel Fairness Attack and Defense Framework Anshuman Chhabra Peizhao Li P. Mohapatra Hongfu Liu OOD 21 22 0 04 Oct 2022
Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural Networks Hussain Hussain Meng Cao Sandipan Sikdar D. Helic Elisabeth Lex M. Strohmaier Roman Kern 19 14 0 13 Sep 2022
How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts Haotao Wang Junyuan Hong Jiayu Zhou Zhangyang Wang OOD 56 11 0 04 Jul 2022
How Biased are Your Features?: Computing Fairness Influence Functions with Global Sensitivity Analysis Bishwamittra Ghosh D. Basu Kuldeep S. Meel FaML 4 9 0 01 Jun 2022
Subverting Fair Image Search with Generative Adversarial Perturbations A. Ghosh Matthew Jagielski Chris L. Wilson 19 7 0 05 May 2022
Robust Conversational Agents against Imperceptible Toxicity Triggers Ninareh Mehrabi Ahmad Beirami Fred Morstatter Aram Galstyan AAML 18 32 0 05 May 2022
Fairness in Graph Mining: A Survey Yushun Dong Jing Ma Song Wang Chen Chen Jundong Li FaML 34 112 0 21 Apr 2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability Enyan Dai Tianxiang Zhao Huaisheng Zhu Jun Xu Zhimeng Guo Hui Liu Jiliang Tang Suhang Wang 29 132 0 18 Apr 2022
Breaking Fair Binary Classification with Optimal Flipping Attacks Changhun Jo Jy-yong Sohn Kangwook Lee FaML 17 7 0 12 Apr 2022
Towards Multi-Objective Statistically Fair Federated Learning Ninareh Mehrabi Cyprien de Lichy John McKay C. He William Campbell FedML 27 9 0 24 Jan 2022
Interpretable Data-Based Explanations for Fairness Debugging Romila Pradhan Jiongli Zhu Boris Glavic Babak Salimi 16 53 0 17 Dec 2021
Fairness Degrading Adversarial Attacks Against Clustering Algorithms Anshuman Chhabra Adish Singla P. Mohapatra 13 7 0 22 Oct 2021
Poisoning Attacks on Fair Machine Learning Minh-Hao Van Wei Du Xintao Wu Aidong Lu AAML 6 23 0 17 Oct 2021
Machine Learning for Fraud Detection in E-Commerce: A Research Agenda Niek Tax Kees Jan de Vries Mathijs de Jong Nikoleta Dosoula Bram van den Akker Jon Smith Olivier Thuong Lucas Bernardi 6 19 0 05 Jul 2021
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data Eugenia Iofinova Nikola Konstantinov Christoph H. Lampert FaML 28 0 0 22 Jun 2021
Fairness-Aware PAC Learning from Corrupted Data Nikola Konstantinov Christoph H. Lampert 11 17 0 11 Feb 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 323 4,203 0 23 Aug 2019
Fairness Constraints: Mechanisms for Fair Classification Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi FaML 114 49 0 19 Jul 2015