Evasion and Hardening of Tree Ensemble Classifiers

25 September 2015

Papers citing "Evasion and Hardening of Tree Ensemble Classifiers"

39 / 39 papers shown

Title
Verifiable Boosted Tree Ensembles Stefano Calzavara Lorenzo Cazzaro Claudio Lucchese Giulio Ermanno Pibiri AAML 44 0 0 22 Feb 2024
Robustness Verification for Knowledge-Based Logic of Risky Driving Scenes Xia Wang Anda Liang Jonathan Sprinkle Taylor T. Johnson 29 4 0 27 Dec 2023
Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification João Vitorino Isabel Praça Eva Maia AAML 37 28 0 30 Jan 2023
Explainable Global Fairness Verification of Tree-Based Classifiers Stefano Calzavara Lorenzo Cazzaro Claudio Lucchese Federico Marcuzzi 40 2 0 27 Sep 2022
Adversarial Robustness for Tabular Data through Cost and Utility Awareness Klim Kireev B. Kulynych Carmela Troncoso AAML 26 16 0 27 Aug 2022
Provably Adversarially Robust Nearest Prototype Classifiers Václav Voráček Matthias Hein AAML 25 11 0 14 Jul 2022
(De-)Randomized Smoothing for Decision Stump Ensembles Miklós Z. Horváth Mark Niklas Muller Marc Fischer Martin Vechev 30 3 0 27 May 2022
Do You Think You Can Hold Me? The Real Challenge of Problem-Space Evasion Attacks Harel Berger A. Dvir Chen Hajaj Rony Ronen AAML 29 3 0 09 May 2022
Beyond Robustness: Resilience Verification of Tree-Based Classifiers Stefano Calzavara Lorenzo Cazzaro Claudio Lucchese Federico Marcuzzi S. Orlando AAML 43 9 0 05 Dec 2021
Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems Giovanni Apruzzese M. Andreolini Luca Ferretti Mirco Marchetti M. Colajanni AAML 34 105 0 17 Jun 2021
A Review of Formal Methods applied to Machine Learning Caterina Urban Antoine Miné 46 55 0 06 Apr 2021
Connecting Interpretability and Robustness in Decision Trees through Separation Michal Moshkovitz Yao-Yuan Yang Kamalika Chaudhuri 33 22 0 14 Feb 2021
Efficient Training of Robust Decision Trees Against Adversarial Examples D. Vos S. Verwer AAML 6 36 0 18 Dec 2020
Omni: Automated Ensemble with Unexpected Models against Adversarial Evasion Attack Rui Shu Tianpei Xia Laurie A. Williams Tim Menzies AAML 32 15 0 23 Nov 2020
Not All Datasets Are Born Equal: On Heterogeneous Data and Adversarial Examples Yael Mathov Eden Levy Ziv Katzir A. Shabtai Yuval Elovici AAML 33 14 0 07 Oct 2020
Certifying Decision Trees Against Evasion Attacks by Program Analysis Stefano Calzavara Pietro Ferrara Claudio Lucchese AAML 29 10 0 06 Jul 2020
Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data Lu Wang Huan Zhang Jinfeng Yi Cho-Jui Hsieh Yuan Jiang AAML 35 12 0 11 May 2020
Complaint-driven Training Data Debugging for Query 2.0 Weiyuan Wu Lampros Flokas Eugene Wu Jiannan Wang 32 43 0 12 Apr 2020
When are Non-Parametric Methods Robust? Robi Bhattacharjee Kamalika Chaudhuri AAML 44 27 0 13 Mar 2020
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable Bytes Keane Lucas Mahmood Sharif Lujo Bauer Michael K. Reiter S. Shintre AAML 31 67 0 19 Dec 2019
Defending Against Adversarial Attacks Using Random Forests Yifan Ding Liqiang Wang Huan Zhang Jinfeng Yi Deliang Fan Boqing Gong AAML 21 14 0 16 Jun 2019
Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective Lu Wang Xuanqing Liu Jinfeng Yi Zhi-Hua Zhou Cho-Jui Hsieh AAML 31 22 0 10 Jun 2019
Robustness Verification of Tree-based Models Hongge Chen Huan Zhang Si Si Yang Li Duane S. Boning Cho-Jui Hsieh AAML 22 76 0 10 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 28 61 0 08 Jun 2019
Robustness for Non-Parametric Classification: A Generic Attack and Defense Yao-Yuan Yang Cyrus Rashtchian Yizhen Wang Kamalika Chaudhuri SILM AAML 34 42 0 07 Jun 2019
Enhancing Transformation-based Defenses using a Distribution Classifier C. Kou H. Lee E. Chang Teck Khim Ng 37 3 0 01 Jun 2019
On Training Robust PDF Malware Classifiers Yizheng Chen Shiqi Wang Dongdong She Suman Jana AAML 50 68 0 06 Apr 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 31 116 0 27 Feb 2019
Securing Behavior-based Opinion Spam Detection Xingyu Lin Guixiang Ma B. Epureanu Philip S. Yu AAML 14 11 0 09 Nov 2018
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks Ambra Demontis Marco Melis Maura Pintor Matthew Jagielski Battista Biggio Alina Oprea Cristina Nita-Rotaru Fabio Roli SILM AAML 19 11 0 08 Sep 2018
On the Suitability of $L_p$ -norms for Creating and Preventing Adversarial Examples Mahmood Sharif Lujo Bauer Michael K. Reiter AAML 24 138 0 27 Feb 2018
DARTS: Deceiving Autonomous Cars with Toxic Signs Chawin Sitawarin A. Bhagoji Arsalan Mosenia M. Chiang Prateek Mittal AAML 37 233 0 18 Feb 2018
A General Framework for Adversarial Examples with Objectives Mahmood Sharif Sruti Bhagavatula Lujo Bauer Michael K. Reiter AAML GAN 13 191 0 31 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 40 1,391 0 08 Dec 2017
Hardening Quantum Machine Learning Against Adversaries N. Wiebe Ramnath Kumar AAML 25 20 0 17 Nov 2017
Resilient Linear Classification: An Approach to Deal with Attacks on Training Data Sangdon Park James Weimer Insup Lee AAML 11 6 0 10 Aug 2017
Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware Davide Maiorca Battista Biggio 15 36 0 17 Jul 2017
Limited-Memory Matrix Adaptation for Large Scale Black-box Optimization I. Loshchilov Tobias Glasmachers Hans-Georg Beyer ODL 30 18 0 18 May 2017
A General Retraining Framework for Scalable Adversarial Classification Bo Li Yevgeniy Vorobeychik Xinyun Chen AAML 21 32 0 09 Apr 2016