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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
The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks F. Assion Peter Schlicht Florens Greßner W. Günther Fabian Hüger Nico M. Schmidt Umair Rasheed AAML 75 14 0 17 Jun 2019
Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective Lu Wang Xuanqing Liu Jinfeng Yi Zhi Zhou Cho-Jui Hsieh AAML 83 22 0 10 Jun 2019
Do Image Classifiers Generalize Across Time? Vaishaal Shankar Achal Dave Rebecca Roelofs Deva Ramanan Benjamin Recht Ludwig Schmidt 142 83 0 05 Jun 2019
Architecture Selection via the Trade-off Between Accuracy and Robustness Zhun Deng Cynthia Dwork Jialiang Wang Yao-Min Zhao AAML 98 3 0 04 Jun 2019
Voice Mimicry Attacks Assisted by Automatic Speaker Verification Ville Vestman Tomi Kinnunen Rosa González Hautamäki Md. Sahidullah 84 37 0 03 Jun 2019
The Adversarial Machine Learning Conundrum: Can The Insecurity of ML Become The Achilles' Heel of Cognitive Networks? Muhammad Usama Junaid Qadir Ala I. Al-Fuqaha M. Hamdi AAML 48 19 0 03 Jun 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 130 754 0 31 May 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward A. Qayyum Muhammad Usama Junaid Qadir Ala I. Al-Fuqaha AAML 94 191 0 29 May 2019
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness Saeed Mahloujifar Xiao Zhang Mohammad Mahmoody David Evans 64 22 0 29 May 2019
Adversarial Robustness Guarantees for Classification with Gaussian Processes Arno Blaas A. Patané Luca Laurenti L. Cardelli Marta Z. Kwiatkowska Stephen J. Roberts GP AAML 89 21 0 28 May 2019
Adversarially Robust Learning Could Leverage Computational Hardness Sanjam Garg S. Jha Saeed Mahloujifar Mohammad Mahmoody AAML 163 24 0 28 May 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 88 248 0 24 May 2019
Predicting Model Failure using Saliency Maps in Autonomous Driving Systems Sina Mohseni Akshay V. Jagadeesh Zhangyang Wang 78 14 0 19 May 2019
Genuinely Distributed Byzantine Machine Learning El-Mahdi El-Mhamdi R. Guerraoui Arsany Guirguis Lê Nguyên Hoang Sébastien Rouault FedML OOD 68 19 0 05 May 2019
Detecting Adversarial Examples through Nonlinear Dimensionality Reduction Francesco Crecchi D. Bacciu Battista Biggio AAML 83 10 0 30 Apr 2019
CryptoNN: Training Neural Networks over Encrypted Data Runhua Xu J. Joshi Chong Li 64 76 0 15 Apr 2019
Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks David J. Miller Zhen Xiang G. Kesidis AAML 74 35 0 12 Apr 2019
Malware Evasion Attack and Defense Yonghong Huang Utkarsh Verma Celeste Fralick G. Infante-Lopez B. Kumar Carl Woodward AAML 65 16 0 07 Apr 2019
Statistical Guarantees for the Robustness of Bayesian Neural Networks L. Cardelli Marta Kwiatkowska Luca Laurenti Nicola Paoletti A. Patané Matthew Wicker AAML 89 54 0 05 Mar 2019
TamperNN: Efficient Tampering Detection of Deployed Neural Nets Erwan Le Merrer Gilles Tredan MLAU AAML 21 9 0 01 Mar 2019
Quantifying Perceptual Distortion of Adversarial Examples Matt Jordan N. Manoj Surbhi Goel A. Dimakis 68 39 0 21 Feb 2019
There are No Bit Parts for Sign Bits in Black-Box Attacks Abdullah Al-Dujaili Una-May O’Reilly AAML 116 20 0 19 Feb 2019
Do ImageNet Classifiers Generalize to ImageNet? Benjamin Recht Rebecca Roelofs Ludwig Schmidt Vaishaal Shankar OOD SSeg VLM 138 1,732 0 13 Feb 2019
When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks Chao-Han Huck Yang Yi-Chieh Liu Pin-Yu Chen Xiaoli Ma Y. Tsai BDL AAML CML 80 21 0 09 Feb 2019
On the security relevance of weights in deep learning Kathrin Grosse T. A. Trost Marius Mosbach Michael Backes Dietrich Klakow AAML 58 6 0 08 Feb 2019
Computational Limitations in Robust Classification and Win-Win Results Akshay Degwekar Preetum Nakkiran Vinod Vaikuntanathan 67 39 0 04 Feb 2019
The Efficacy of SHIELD under Different Threat Models Cory Cornelius Nilaksh Das Shang-Tse Chen Li Chen Michael E. Kounavis Duen Horng Chau AAML 71 11 0 01 Feb 2019
Optimal Attack against Autoregressive Models by Manipulating the Environment Yiding Chen Xiaojin Zhu AAML 53 11 0 01 Feb 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise Nic Ford Justin Gilmer Nicholas Carlini E. D. Cubuk AAML 132 320 0 29 Jan 2019
RED-Attack: Resource Efficient Decision based Attack for Machine Learning Faiq Khalid Hassan Ali Muhammad Abdullah Hanif Semeen Rehman Rehan Ahmed Mohamed Bennai AAML 71 14 0 29 Jan 2019
Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey W. Zhang Quan Z. Sheng A. Alhazmi Chenliang Li AAML 114 57 0 21 Jan 2019
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries Christian Scano Battista Biggio Giovanni Lagorio Fabio Roli A. Armando AAML 80 131 0 11 Jan 2019
Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification L. G. Hafemann R. Sabourin Luiz Eduardo Soares de Oliveira AAML 55 44 0 10 Jan 2019
Towards resilient machine learning for ransomware detection Li-Wei Chen Chih-Yuan Yang Anindya Paul R. Sahita AAML 36 22 0 21 Dec 2018
PROVEN: Certifying Robustness of Neural Networks with a Probabilistic Approach Tsui-Wei Weng Pin-Yu Chen Lam M. Nguyen M. Squillante Ivan Oseledets Luca Daniel AAML 82 30 0 18 Dec 2018
Training Set Camouflage Ayon Sen Scott Alfeld Xuezhou Zhang Ara Vartanian Yuzhe Ma Xiaojin Zhu 13 7 0 13 Dec 2018
Adversarial Attacks, Regression, and Numerical Stability Regularization A. Nguyen Edward Raff AAML 52 30 0 07 Dec 2018
The Limitations of Model Uncertainty in Adversarial Settings Kathrin Grosse David Pfaff M. Smith Michael Backes AAML 63 34 0 06 Dec 2018
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 138 173 0 03 Dec 2018
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 311 285 0 03 Dec 2018
Model-Reuse Attacks on Deep Learning Systems Yujie Ji Xinyang Zhang S. Ji Xiapu Luo Ting Wang SILM AAML 189 187 0 02 Dec 2018
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 102 92 0 01 Dec 2018
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks Akhilan Boopathy Tsui-Wei Weng Pin-Yu Chen Sijia Liu Luca Daniel AAML 158 138 0 29 Nov 2018
Bilateral Adversarial Training: Towards Fast Training of More Robust Models Against Adversarial Attacks Jianyu Wang Haichao Zhang OOD AAML 87 119 0 26 Nov 2018
Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses Jérôme Rony L. G. Hafemann Luiz Eduardo Soares de Oliveira Ismail Ben Ayed R. Sabourin Eric Granger AAML 78 299 0 23 Nov 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 72 68 0 13 Nov 2018
An Optimal Control View of Adversarial Machine Learning Xiaojin Zhu AAML 55 25 0 11 Nov 2018
Can We Use Speaker Recognition Technology to Attack Itself? Enhancing Mimicry Attacks Using Automatic Target Speaker Selection Tomi Kinnunen Rosa González Hautamäki Ville Vestman Md. Sahidullah 70 5 0 09 Nov 2018
FAdeML: Understanding the Impact of Pre-Processing Noise Filtering on Adversarial Machine Learning Faiq Khalid Muhammad Abdullah Hanif Semeen Rehman Junaid Qadir Mohamed Bennai AAML 85 34 0 04 Nov 2018
Efficient Neural Network Robustness Certification with General Activation Functions Huan Zhang Tsui-Wei Weng Pin-Yu Chen Cho-Jui Hsieh Luca Daniel AAML 124 765 0 02 Nov 2018