Poisoning Attacks on Algorithmic Fairness

Poisoning Attacks on Algorithmic Fairness

15 April 2020

Battista Biggio

Carlos Castillo

Papers citing "Poisoning Attacks on Algorithmic Fairness"

16 / 16 papers shown

Title
Covert Attacks on Machine Learning Training in Passively Secure MPC Matthew Jagielski Daniel Escudero Rahul Rachuri Peter Scholl 41 0 0 21 May 2025
FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding? Marco Bornstein Amrit Singh Bedi Abdirisak Mohamed Furong Huang FedML 59 0 0 22 May 2024
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 275 493 0 31 Dec 2020
POTs: Protective Optimization Technologies B. Kulynych R. Overdorf Carmela Troncoso Seda F. Gürses 28 96 0 07 Jun 2018
Is feature selection secure against training data poisoning? Huang Xiao Battista Biggio Gavin Brown Giorgio Fumera Claudia Eckert Fabio Roli AAML SILM 36 423 0 21 Apr 2018
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning Matthew Jagielski Alina Oprea Battista Biggio Chang-rui Liu Cristina Nita-Rotaru Yue Liu AAML 57 757 0 01 Apr 2018
A comparative study of fairness-enhancing interventions in machine learning Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian Sonam Choudhary Evan P. Hamilton Derek Roth FaML 88 639 0 13 Feb 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 85 1,401 0 08 Dec 2017
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization Luis Muñoz-González Battista Biggio Ambra Demontis Andrea Paudice Vasin Wongrassamee Emil C. Lupu Fabio Roli AAML 85 628 0 29 Aug 2017
From Parity to Preference-based Notions of Fairness in Classification Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi Adrian Weller FaML 58 209 0 30 Jun 2017
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi FaML 116 1,204 0 26 Oct 2016
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 285 2,098 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 105 4,276 0 07 Oct 2016
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples Nicolas Papernot Patrick McDaniel Ian Goodfellow SILM AAML 78 1,735 0 24 May 2016
Certifying and removing disparate impact Michael Feldman Sorelle A. Friedler John Moeller C. Scheidegger Suresh Venkatasubramanian FaML 112 1,978 0 11 Dec 2014
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 80 1,580 0 27 Jun 2012