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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
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor Aleksander Madry 139 428 0 16 Jul 2020
A Survey of Privacy Attacks in Machine Learning M. Rigaki Sebastian Garcia PILM AAML 117 226 0 15 Jul 2020
Adversarial Examples and Metrics Nico Döttling Kathrin Grosse Michael Backes Ian Molloy AAML 49 0 0 14 Jul 2020
Improved Detection of Adversarial Images Using Deep Neural Networks Yutong Gao Yi-Lun Pan AAML 56 3 0 10 Jul 2020
Certifying Decision Trees Against Evasion Attacks by Program Analysis Stefano Calzavara Pietro Ferrara Claudio Lucchese AAML 60 10 0 06 Jul 2020
On Data Augmentation and Adversarial Risk: An Empirical Analysis Hamid Eghbalzadeh Khaled Koutini Paul Primus Verena Haunschmid Michal Lewandowski Werner Zellinger Bernhard A. Moser Gerhard Widmer AAML 42 9 0 06 Jul 2020
Understanding and Improving Fast Adversarial Training Maksym Andriushchenko Nicolas Flammarion AAML 94 294 0 06 Jul 2020
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain Ishai Rosenberg A. Shabtai Yuval Elovici Lior Rokach AAML 85 12 0 05 Jul 2020
Adversarial Deep Ensemble: Evasion Attacks and Defenses for Malware Detection Deqiang Li Qianmu Li AAML 77 126 0 30 Jun 2020
Best-Effort Adversarial Approximation of Black-Box Malware Classifiers A. Ali Birhanu Eshete AAML 34 6 0 28 Jun 2020
Bit Error Robustness for Energy-Efficient DNN Accelerators David Stutz Nandhini Chandramoorthy Matthias Hein Bernt Schiele MQ 52 1 0 24 Jun 2020
X-ModalNet: A Semi-Supervised Deep Cross-Modal Network for Classification of Remote Sensing Data Danfeng Hong Naoto Yokoya Gui-Song Xia J. Chanussot X. Zhu 39 55 0 24 Jun 2020
With Great Dispersion Comes Greater Resilience: Efficient Poisoning Attacks and Defenses for Linear Regression Models Jialin Wen Benjamin Zi Hao Zhao Minhui Xue Alina Oprea Hai-feng Qian AAML 70 20 0 21 Jun 2020
Graph Backdoor Zhaohan Xi Ren Pang S. Ji Ting Wang AI4CE AAML 72 172 0 21 Jun 2020
The Dilemma Between Data Transformations and Adversarial Robustness for Time Series Application Systems Sheila Alemany N. Pissinou AAML 20 8 0 18 Jun 2020
A Survey of Machine Learning Methods and Challenges for Windows Malware Classification Edward Raff Charles K. Nicholas AAML 70 57 0 15 Jun 2020
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data Zhun Deng Linjun Zhang Amirata Ghorbani James Zou 90 32 0 15 Jun 2020
Defending SVMs against Poisoning Attacks: the Hardness and DBSCAN Approach Hu Ding Fan Yang Jiawei Huang AAML 15 0 0 14 Jun 2020
Backdoor Smoothing: Demystifying Backdoor Attacks on Deep Neural Networks Kathrin Grosse Taesung Lee Battista Biggio Youngja Park Michael Backes Ian Molloy AAML 39 10 0 11 Jun 2020
Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors Gerda Bortsova C. González-Gonzalo S. Wetstein Florian Dubost Ioannis Katramados ... Bram van Ginneken J. Pluim M. Veta Clara I. Sánchez Marleen de Bruijne AAML MedIm 38 131 0 11 Jun 2020
Trade-offs between membership privacy & adversarially robust learning Jamie Hayes SILM 54 3 0 08 Jun 2020
Consistency Regularization for Certified Robustness of Smoothed Classifiers Jongheon Jeong Jinwoo Shin AAML 86 88 0 07 Jun 2020
Unique properties of adversarially trained linear classifiers on Gaussian data Jamie Hayes AAML 75 0 0 06 Jun 2020
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers S. Melacci Gabriele Ciravegna Angelo Sotgiu Ambra Demontis Battista Biggio Marco Gori Fabio Roli 88 15 0 06 Jun 2020
Generating Artificial Outliers in the Absence of Genuine Ones -- a Survey Georg Steinbuss Klemens Böhm 54 8 0 05 Jun 2020
Sponge Examples: Energy-Latency Attacks on Neural Networks Ilia Shumailov Yiren Zhao Daniel Bates Nicolas Papernot Robert D. Mullins Ross J. Anderson SILM 81 138 0 05 Jun 2020
Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack Methods Kyungmi Lee A. Chandrakasan ELM AAML 69 3 0 01 Jun 2020
Keyed Non-Parametric Hypothesis Tests Yao Cheng Cheng-Kang Chu Hsiao-Ying Lin Marius Lombard-Platet D. Naccache AAML 6 0 0 25 May 2020
Adversarial Attack on Hierarchical Graph Pooling Neural Networks Haoteng Tang Guixiang Ma Yurong Chen Lei Guo Wei Wang Bo Zeng Liang Zhan AAML 93 28 0 23 May 2020
Reliability and Robustness analysis of Machine Learning based Phishing URL Detectors Bushra Sabir Muhammad Ali Babar R. Gaire A. Abuadbba AAML 86 10 0 18 May 2020
Encryption Inspired Adversarial Defense for Visual Classification Maungmaung Aprilpyone Hitoshi Kiya 56 32 0 16 May 2020
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning Pieter Delobelle Paul Temple Gilles Perrouin Benoit Frénay P. Heymans Bettina Berendt AAML FaML 134 16 0 14 May 2020
Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data Lu Wang Huan Zhang Jinfeng Yi Cho-Jui Hsieh Yuan Jiang AAML 82 12 0 11 May 2020
Blind Backdoors in Deep Learning Models Eugene Bagdasaryan Vitaly Shmatikov AAML FedML SILM 160 310 0 08 May 2020
Adversarial Training against Location-Optimized Adversarial Patches Sukrut Rao David Stutz Bernt Schiele AAML 84 92 0 05 May 2020
Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware? Marco Melis Michele Scalas Ambra Demontis Davide Maiorca Battista Biggio Giorgio Giacinto Fabio Roli AAML FAtt 54 28 0 04 May 2020
Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness Pu Zhao Pin-Yu Chen Payel Das Karthikeyan N. Ramamurthy Xue Lin AAML 149 191 0 30 Apr 2020
Bias Busters: Robustifying DL-based Lithographic Hotspot Detectors Against Backdooring Attacks Kang Liu Benjamin Tan Gaurav Rajavendra Reddy S. Garg Yiorgos Makris Ramesh Karri AAML 49 9 0 26 Apr 2020
A Black-box Adversarial Attack Strategy with Adjustable Sparsity and Generalizability for Deep Image Classifiers Arka Ghosh S. S. Mullick Shounak Datta Swagatam Das R. Mallipeddi A. Das AAML 63 38 0 24 Apr 2020
Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers Loc Truong Chace Jones Brian Hutchinson Andrew August Brenda Praggastis Robert J. Jasper Nicole Nichols Aaron Tuor AAML 68 52 0 24 Apr 2020
Probabilistic Safety for Bayesian Neural Networks Matthew Wicker Luca Laurenti A. Patané Marta Z. Kwiatkowska AAML 61 52 0 21 Apr 2020
The Attacker's Perspective on Automatic Speaker Verification: An Overview Rohan Kumar Das Xiaohai Tian Tomi Kinnunen Haizhou Li AAML 66 80 0 19 Apr 2020
Protecting Classifiers From Attacks. A Bayesian Approach Víctor Gallego Roi Naveiro A. Redondo D. Insua Fabrizio Ruggeri AAML 13 2 0 18 Apr 2020
Poisoning Attacks on Algorithmic Fairness David Solans Battista Biggio Carlos Castillo AAML 84 82 0 15 Apr 2020
Feature Partitioning for Robust Tree Ensembles and their Certification in Adversarial Scenarios Stefano Calzavara Claudio Lucchese Federico Marcuzzi S. Orlando AAML 45 9 0 07 Apr 2020
Adversarial Genetic Programming for Cyber Security: A Rising Application Domain Where GP Matters Una-May O’Reilly J. Toutouh M. Pertierra Daniel Prado Sanchez Dennis Garcia Anthony Erb Luogo Jonathan Kelly Erik Hemberg SILM AAML 52 30 0 07 Apr 2020
Functionality-preserving Black-box Optimization of Adversarial Windows Malware Christian Scano Battista Biggio Giovanni Lagorio Fabio Roli A. Armando AAML 87 146 0 30 Mar 2020
Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning Amin Rakhsha Goran Radanović R. Devidze Xiaojin Zhu Adish Singla AAML OffRL 99 125 0 28 Mar 2020
A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks Samuel Deng Sanjam Garg S. Jha Saeed Mahloujifar Mohammad Mahmoody Abhradeep Thakurta 30 3 0 26 Mar 2020
Vulnerabilities of Connectionist AI Applications: Evaluation and Defence Christian Berghoff Matthias Neu Arndt von Twickel AAML 109 25 0 18 Mar 2020