Adversarial Robustness for Tabular Data through Cost and Utility Awareness

27 August 2022

Papers citing "Adversarial Robustness for Tabular Data through Cost and Utility Awareness"

47 / 47 papers shown

Title
CaFA: Cost-aware, Feasible Attacks With Database Constraints Against Neural Tabular Classifiers Matan Ben-Tov Daniel Deutch Nave Frost Mahmood Sharif AAML 165 0 0 20 Jan 2025
On the effectiveness of adversarial training against common corruptions Klim Kireev Maksym Andriushchenko Nicolas Flammarion AAML 56 103 0 03 Mar 2021
Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data F. Cartella Orlando Anunciação Yuki Funabiki D. Yamaguchi Toru Akishita Olivier Elshocht AAML 94 75 0 20 Jan 2021
Efficient Training of Robust Decision Trees Against Adversarial Examples D. Vos S. Verwer AAML 31 36 0 18 Dec 2020
PAC-Learning for Strategic Classification Ravi Sundaram A. Vullikanti Haifeng Xu Fan Yao AAML 67 42 0 06 Dec 2020
Not All Datasets Are Born Equal: On Heterogeneous Data and Adversarial Examples Yael Mathov Eden Levy Ziv Katzir A. Shabtai Yuval Elovici AAML 73 14 0 07 Oct 2020
Efficient Projection Algorithms onto the Weighted l1 Ball Guillaume Perez Sebastian Ament Carla P. Gomes Michel Barlaud 22 9 0 07 Sep 2020
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models Cassidy Laidlaw Sahil Singla Soheil Feizi AAML OOD 77 187 0 22 Jun 2020
A Causal View on Robustness of Neural Networks Cheng Zhang Kun Zhang Yingzhen Li CML OOD 69 86 0 03 May 2020
Politics of Adversarial Machine Learning Kendra Albert J. Penney B. Schneier Ramnath Kumar AAML 53 19 0 01 Feb 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 134 1,175 0 12 Jan 2020
T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack Wei Ping Hengzhi Pei Boyuan Pan Han Liu Shuohang Wang Yangqiu Song AAML 35 6 0 22 Dec 2019
Imperceptible Adversarial Attacks on Tabular Data Vincent Ballet X. Renard Jonathan Aigrain Thibault Laugel P. Frossard Marcin Detyniecki 68 73 0 08 Nov 2019
Strategic Classification is Causal Modeling in Disguise John Miller S. Milli Moritz Hardt 56 112 0 23 Oct 2019
Adversarial Robustness Against the Union of Multiple Perturbation Models Pratyush Maini Eric Wong J. Zico Kolter OOD AAML 47 151 0 09 Sep 2019
TabNet: Attentive Interpretable Tabular Learning Sercan O. Arik Tomas Pfister LMTD 157 1,343 0 20 Aug 2019
Treant: Training Evasion-Aware Decision Trees Stefano Calzavara Claudio Lucchese Gabriele Tolomei S. Abebe S. Orlando AAML 57 41 0 02 Jul 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 62 61 0 08 Jun 2019
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 125 1,245 0 29 Apr 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 100 117 0 27 Feb 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations Eric Wong Frank R. Schmidt J. Zico Kolter AAML 67 211 0 21 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 127 2,542 0 24 Jan 2019
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification Qi Lei Lingfei Wu Pin-Yu Chen A. Dimakis Inderjit S. Dhillon Michael Witbrock AAML 50 92 0 01 Dec 2018
Evading classifiers in discrete domains with provable optimality guarantees B. Kulynych Jamie Hayes N. Samarin Carmela Troncoso AAML 46 20 0 25 Oct 2018
Cost-Sensitive Robustness against Adversarial Examples Xiao Zhang David Evans AAML 43 24 0 22 Oct 2018
The Social Cost of Strategic Classification S. Milli John Miller Anca Dragan Moritz Hardt 47 181 0 25 Aug 2018
POTs: Protective Optimization Technologies B. Kulynych R. Overdorf Carmela Troncoso Seda F. Gürses 30 96 0 07 Jun 2018
Scaling provable adversarial defenses Eric Wong Frank R. Schmidt J. H. Metzen J. Zico Kolter AAML 70 446 0 31 May 2018
Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Michael I. Jordan AAML SILM 84 116 0 31 May 2018
AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning Jinyuan Jia Neil Zhenqiang Gong AAML 57 164 0 13 May 2018
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables Bojan Kolosnjaji Ambra Demontis Battista Biggio Davide Maiorca Giorgio Giacinto Claudia Eckert Fabio Roli AAML 49 317 0 12 Mar 2018
On the Suitability of $L_p$ -norms for Creating and Preventing Adversarial Examples Mahmood Sharif Lujo Bauer Michael K. Reiter AAML 125 138 0 27 Feb 2018
DARTS: Deceiving Autonomous Cars with Toxic Signs Chawin Sitawarin A. Bhagoji Arsalan Mosenia M. Chiang Prateek Mittal AAML 86 235 0 18 Feb 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 106 1,407 0 08 Dec 2017
Strategic Classification from Revealed Preferences Jinshuo Dong Aaron Roth Zachary Schutzman Bo Waggoner Zhiwei Steven Wu 72 178 0 22 Oct 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 277 12,029 0 19 Jun 2017
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection Ambra Demontis Marco Melis Battista Biggio Davide Maiorca Dan Arp Konrad Rieck Igino Corona Giorgio Giacinto Fabio Roli AAML 49 284 0 28 Apr 2017
Deep Text Classification Can be Fooled Bin Liang Hongcheng Li Miaoqiang Su Pan Bian Xirong Li Wenchang Shi AAML 73 424 0 26 Apr 2017
On the (Statistical) Detection of Adversarial Examples Kathrin Grosse Praveen Manoharan Nicolas Papernot Michael Backes Patrick McDaniel AAML 73 712 0 21 Feb 2017
Towards the Science of Security and Privacy in Machine Learning Nicolas Papernot Patrick McDaniel Arunesh Sinha Michael P. Wellman AAML 77 473 0 11 Nov 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 237 8,548 0 16 Aug 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 88 3,955 0 24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 131 4,886 0 14 Nov 2015
Evasion and Hardening of Tree Ensemble Classifiers Alex Kantchelian J. D. Tygar A. Joseph AAML 109 205 0 25 Sep 2015
Strategic Classification Moritz Hardt N. Megiddo Christos H. Papadimitriou Mary Wootters 62 371 0 23 Jun 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 241 19,017 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 247 14,893 1 21 Dec 2013