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Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning

8 December 2017

Battista Biggio

Fabio Roli

AAML

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Papers citing "Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning"

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Title
A Survey of Adversarial Learning on Graphs Liang Chen Jintang Li Jiaying Peng Tao Xie Zengxu Cao Kun Xu Xiangnan He Zibin Zheng Bingzhe Wu AAML 107 85 0 10 Mar 2020
Adversarial Machine Learning: Bayesian Perspectives D. Insua Roi Naveiro Víctor Gallego Jason Poulos AAML 27 21 0 07 Mar 2020
Optimal Feature Manipulation Attacks Against Linear Regression Fuwei Li Lifeng Lai Shuguang Cui AAML 49 2 0 29 Feb 2020
The Effectiveness of Johnson-Lindenstrauss Transform for High Dimensional Optimization With Adversarial Outliers, and the Recovery Hu Ding Ruizhe Qin Jiawei Huang AAML 23 0 0 27 Feb 2020
Polarizing Front Ends for Robust CNNs Can Bakiskan S. Gopalakrishnan Metehan Cekic Upamanyu Madhow Ramtin Pedarsani AAML 45 4 0 22 Feb 2020
NNoculation: Catching BadNets in the Wild A. Veldanda Kang Liu Benjamin Tan Prashanth Krishnamurthy Farshad Khorrami Ramesh Karri Brendan Dolan-Gavitt S. Garg AAML OnRL 82 20 0 19 Feb 2020
Robustness of Bayesian Neural Networks to Gradient-Based Attacks Ginevra Carbone Matthew Wicker Luca Laurenti A. Patané Luca Bortolussi G. Sanguinetti AAML 104 79 0 11 Feb 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers Thomas Baumhauer Pascal Schöttle Matthias Zeppelzauer MU 176 133 0 07 Feb 2020
Politics of Adversarial Machine Learning Kendra Albert J. Penney B. Schneier Ramnath Kumar AAML 119 20 0 01 Feb 2020
Media Forensics and DeepFakes: an overview L. Verdoliva 110 555 0 18 Jan 2020
WAF-A-MoLE: Evading Web Application Firewalls through Adversarial Machine Learning Christian Scano Biagio Montaruli Gabriele Costa Giovanni Lagorio AAML 59 29 0 07 Jan 2020
ATHENA: A Framework based on Diverse Weak Defenses for Building Adversarial Defense Meng Jianhai Su Jason M. O'Kane Pooyan Jamshidi AAML 57 7 0 02 Jan 2020
Quantum Adversarial Machine Learning Sirui Lu L. Duan D. Deng AAML 108 102 0 31 Dec 2019
A Gentle Introduction to Deep Learning for Graphs D. Bacciu Federico Errica Alessio Micheli Marco Podda AI4CE GNN 135 281 0 29 Dec 2019
secml: A Python Library for Secure and Explainable Machine Learning Maura Pintor Christian Scano Angelo Sotgiu Marco Melis Ambra Demontis Battista Biggio AAML 93 15 0 20 Dec 2019
Does Symbolic Knowledge Prevent Adversarial Fooling? Stefano Teso GAN AAML 23 2 0 19 Dec 2019
Square Attack: a query-efficient black-box adversarial attack via random search Maksym Andriushchenko Francesco Croce Nicolas Flammarion Matthias Hein AAML 148 997 0 29 Nov 2019
FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles Ana Lucic Harrie Oosterhuis H. Haned Maarten de Rijke LRM 104 63 0 27 Nov 2019
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 95 70 0 06 Nov 2019
Intriguing Properties of Adversarial ML Attacks in the Problem Space [Extended Version] Jacopo Cortellazzi Feargus Pendlebury Daniel Arp Erwin Quiring Fabio Pierazzi Lorenzo Cavallaro AAML 92 0 0 05 Nov 2019
A Tale of Evil Twins: Adversarial Inputs versus Poisoned Models Ren Pang Hua Shen Xinyang Zhang S. Ji Yevgeniy Vorobeychik Xiaopu Luo Alex Liu Ting Wang AAML 55 2 0 05 Nov 2019
Investigating Resistance of Deep Learning-based IDS against Adversaries using min-max Optimization Rana Abou-Khamis Omair Shafiq Ashraf Matrawy AAML 101 40 0 30 Oct 2019
Differentiable Convex Optimization Layers Akshay Agrawal Brandon Amos Shane T. Barratt Stephen P. Boyd Steven Diamond Zico Kolter 102 666 0 28 Oct 2019
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks David Stutz Matthias Hein Bernt Schiele AAML 89 5 0 14 Oct 2019
Policy Poisoning in Batch Reinforcement Learning and Control Yuzhe Ma Xuezhou Zhang Wen Sun Xiaojin Zhu AAML OffRL 88 115 0 13 Oct 2019
Would a File by Any Other Name Seem as Malicious? A. Nguyen Edward Raff Aaron Sant-Miller AAML 40 7 0 10 Oct 2019
Deep Neural Rejection against Adversarial Examples Angelo Sotgiu Ambra Demontis Marco Melis Battista Biggio Giorgio Fumera Xiaoyi Feng Fabio Roli AAML 88 69 0 01 Oct 2019
Cross-Layer Strategic Ensemble Defense Against Adversarial Examples Wenqi Wei Ling Liu Margaret Loper Ka-Ho Chow Emre Gursoy Stacey Truex Yanzhao Wu AAML 52 12 0 01 Oct 2019
Lower Bounds on Adversarial Robustness from Optimal Transport A. Bhagoji Daniel Cullina Prateek Mittal OOD OT AAML 70 94 0 26 Sep 2019
A Visual Analytics Framework for Adversarial Text Generation Brandon Laughlin C. Collins K. Sankaranarayanan K. El-Khatib AAML 37 10 0 24 Sep 2019
Generating Black-Box Adversarial Examples for Text Classifiers Using a Deep Reinforced Model Prashanth Vijayaraghavan D. Roy AAML 49 36 0 17 Sep 2019
Towards Quality Assurance of Software Product Lines with Adversarial Configurations Paul Temple M. Acher Gilles Perrouin Battista Biggio J. Jézéquel Fabio Roli AAML 41 11 0 16 Sep 2019
Node Injection Attacks on Graphs via Reinforcement Learning Yiwei Sun Suhang Wang Xianfeng Tang Tsung-Yu Hsieh Vasant Honavar GNN AAML 72 45 0 14 Sep 2019
On the Hardness of Robust Classification Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell 74 44 0 12 Sep 2019
Invisible Backdoor Attacks on Deep Neural Networks via Steganography and Regularization Shaofeng Li Minhui Xue Benjamin Zi Hao Zhao Haojin Zhu Dali Kaafar 85 60 0 06 Sep 2019
VisualPhishNet: Zero-Day Phishing Website Detection by Visual Similarity Sahar Abdelnabi Katharina Krombholz Mario Fritz 44 6 0 01 Sep 2019
Opponent Aware Reinforcement Learning Víctor Gallego Roi Naveiro D. Insua D. Gómez‐Ullate 21 7 0 22 Aug 2019
Human uncertainty makes classification more robust Joshua C. Peterson Ruairidh M. Battleday Thomas Griffiths Olga Russakovsky OOD 72 306 0 19 Aug 2019
Gradient Methods for Solving Stackelberg Games Roi Naveiro D. Insua 55 12 0 19 Aug 2019
Universal Adversarial Audio Perturbations Sajjad Abdoli L. G. Hafemann Jérôme Rony Ismail Ben Ayed P. Cardinal Alessandro Lameiras Koerich AAML 91 52 0 08 Aug 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 112 231 0 24 Jul 2019
Towards Adversarially Robust Object Detection Haichao Zhang Jianyu Wang AAML ObjD 136 131 0 24 Jul 2019
Connecting Lyapunov Control Theory to Adversarial Attacks Arash Rahnama A. Nguyen Edward Raff AAML 21 6 0 17 Jul 2019
Constrained Concealment Attacks against Reconstruction-based Anomaly Detectors in Industrial Control Systems Alessandro Erba Riccardo Taormina S. Galelli Marcello Pogliani Michele Carminati S. Zanero Nils Ole Tippenhauer AAML 81 22 0 17 Jul 2019
Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics Yuxin Ma Tiankai Xie Jundong Li Ross Maciejewski AAML 79 67 0 17 Jul 2019
Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods Arif Siddiqi AAML 64 11 0 17 Jul 2019
Efficient Cyber Attacks Detection in Industrial Control Systems Using Lightweight Neural Networks and PCA Moshe Kravchik A. Shabtai AAML 90 55 0 02 Jul 2019
Treant: Training Evasion-Aware Decision Trees Stefano Calzavara Claudio Lucchese Gabriele Tolomei S. Abebe S. Orlando AAML 75 41 0 02 Jul 2019
The Adversarial Robustness of Sampling Omri Ben-Eliezer E. Yogev TTA AAML 61 48 0 26 Jun 2019
Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection Kang Liu Haoyu Yang Yuzhe Ma Benjamin Tan Bei Yu Evangeline F. Y. Young Ramesh Karri S. Garg AAML 41 10 0 25 Jun 2019