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

8 December 2017

Battista Biggio

Fabio Roli

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

50 / 210 papers shown

Title
Survey: Leakage and Privacy at Inference Time Marija Jegorova Chaitanya Kaul Charlie Mayor Alison Q. OÑeil Alexander Weir Roderick Murray-Smith Sotirios A. Tsaftaris PILM MIACV 21 71 0 04 Jul 2021
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning Anders Andreassen Yasaman Bahri Behnam Neyshabur Rebecca Roelofs OOD OODD 30 78 0 30 Jun 2021
The Threat of Offensive AI to Organizations Yisroel Mirsky Ambra Demontis J. Kotak Ram Shankar Deng Gelei Liu Yang Xinming Zhang Wenke Lee Yuval Elovici Battista Biggio 33 81 0 30 Jun 2021
Feature Importance Guided Attack: A Model Agnostic Adversarial Attack Gilad Gressel Niranjan Hegde A. Sreekumar Rishikumar Radhakrishnan Kalyani Harikumar Michael C. Darling Krishnashree Achuthan AAML 67 16 0 28 Jun 2021
The Feasibility and Inevitability of Stealth Attacks I. Tyukin D. Higham Alexander Bastounis Eliyas Woldegeorgis Alexander N. Gorban AAML 22 19 0 26 Jun 2021
Adversarial Training Helps Transfer Learning via Better Representations Zhun Deng Linjun Zhang Kailas Vodrahalli Kenji Kawaguchi James Zou GAN 36 52 0 18 Jun 2021
Bad Characters: Imperceptible NLP Attacks Nicholas Boucher Ilia Shumailov Ross J. Anderson Nicolas Papernot AAML SILM 41 103 0 18 Jun 2021
Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems Giovanni Apruzzese M. Andreolini Luca Ferretti Mirco Marchetti M. Colajanni AAML 34 104 0 17 Jun 2021
Certification of embedded systems based on Machine Learning: A survey Guillaume Vidot Christophe Gabreau I. Ober Iulian Ober 11 12 0 14 Jun 2021
A BIC-based Mixture Model Defense against Data Poisoning Attacks on Classifiers Xi Li David J. Miller Zhen Xiang G. Kesidis AAML 16 0 0 28 May 2021
Lightweight Distributed Gaussian Process Regression for Online Machine Learning Zhenyuan Yuan Minghui Zhu 21 4 0 11 May 2021
De-Pois: An Attack-Agnostic Defense against Data Poisoning Attacks Jian Chen Xuxin Zhang Rui Zhang Chen Wang Ling Liu AAML 25 86 0 08 May 2021
Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs Théo Lacombe Yuichi Ike Mathieu Carrière Frédéric Chazal Marc Glisse Yuhei Umeda 29 20 0 07 May 2021
Influence Based Defense Against Data Poisoning Attacks in Online Learning Sanjay Seetharaman Shubham Malaviya KV Rosni Manish Shukla S. Lodha TDI AAML 39 9 0 24 Apr 2021
Turning Federated Learning Systems Into Covert Channels Gabriele Costa Fabio Pinelli S. Soderi Gabriele Tolomei FedML 37 10 0 21 Apr 2021
Prospective Artificial Intelligence Approaches for Active Cyber Defence Neil Dhir H. Hoeltgebaum N. Adams M. Briers A. Burke Paul Jones AAML 36 25 0 20 Apr 2021
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators David Stutz Nandhini Chandramoorthy Matthias Hein Bernt Schiele AAML MQ 24 18 0 16 Apr 2021
Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-based Network Intrusion Detection Mohanad Sarhan S. Layeghy Marius Portmann 26 60 0 15 Apr 2021
A Backdoor Attack against 3D Point Cloud Classifiers Zhen Xiang David J. Miller Siheng Chen Xi Li G. Kesidis 3DPC AAML 33 76 0 12 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 32 65 0 09 Apr 2021
Black-box Detection of Backdoor Attacks with Limited Information and Data Yinpeng Dong Xiao Yang Zhijie Deng Tianyu Pang Zihao Xiao Hang Su Jun Zhu AAML 21 112 0 24 Mar 2021
The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers? Antonio Emanuele Cinà Sebastiano Vascon Ambra Demontis Battista Biggio Fabio Roli Marcello Pelillo AAML 27 9 0 23 Mar 2021
Explainable Adversarial Attacks in Deep Neural Networks Using Activation Profiles G. Cantareira R. Mello F. Paulovich AAML 24 9 0 18 Mar 2021
Proof-of-Learning: Definitions and Practice Hengrui Jia Mohammad Yaghini Christopher A. Choquette-Choo Natalie Dullerud Anvith Thudi Varun Chandrasekaran Nicolas Papernot AAML 25 99 0 09 Mar 2021
Pseudo-labeling for Scalable 3D Object Detection Benjamin Caine Rebecca Roelofs Vijay Vasudevan Jiquan Ngiam Yuning Chai Z. Chen Jonathon Shlens 34 41 0 02 Mar 2021
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints Maura Pintor Fabio Roli Wieland Brendel Battista Biggio AAML 51 70 0 25 Feb 2021
Non-Singular Adversarial Robustness of Neural Networks Yu-Lin Tsai Chia-Yi Hsu Chia-Mu Yu Pin-Yu Chen AAML OOD 14 5 0 23 Feb 2021
Universal Adversarial Examples and Perturbations for Quantum Classifiers Weiyuan Gong D. Deng AAML 32 23 0 15 Feb 2021
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS Felix O. Olowononi D. Rawat Chunmei Liu 34 132 0 14 Feb 2021
Defense Against Reward Poisoning Attacks in Reinforcement Learning Kiarash Banihashem Adish Singla Goran Radanović AAML 35 26 0 10 Feb 2021
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Muhammad Shafique Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 81 100 0 04 Jan 2021
Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges Kashif Ahmad Majdi Maabreh M. Ghaly Khalil Khan Junaid Qadir Ala I. Al-Fuqaha 27 142 0 14 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
Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks Amin Rakhsha Goran Radanović R. Devidze Xiaojin Zhu Adish Singla AAML OffRL 28 29 0 21 Nov 2020
Adversarially Robust Classification based on GLRT Bhagyashree Puranik Upamanyu Madhow Ramtin Pedarsani VLM AAML 23 4 0 16 Nov 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
Mischief: A Simple Black-Box Attack Against Transformer Architectures Adrian de Wynter AAML 42 1 0 16 Oct 2020
Reverse Engineering Imperceptible Backdoor Attacks on Deep Neural Networks for Detection and Training Set Cleansing Zhen Xiang David J. Miller G. Kesidis 29 22 0 15 Oct 2020
Pocket Diagnosis: Secure Federated Learning against Poisoning Attack in the Cloud Zhuo Ma Jianfeng Ma Yinbin Miao Ximeng Liu K. Choo R. Deng FedML 20 32 0 23 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 41 62 0 11 Sep 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo-wen Li AAML 33 128 0 09 Sep 2020
Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems Sandhya Saisubramanian S. Zilberstein Ece Kamar 14 21 0 24 Aug 2020
Defending Regression Learners Against Poisoning Attacks Sandamal Weerasinghe S. Erfani T. Alpcan C. Leckie Justin Kopacz AAML 16 0 0 21 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 27 73 0 07 Aug 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor A. Madry 37 417 0 16 Jul 2020
A Survey of Privacy Attacks in Machine Learning M. Rigaki Sebastian Garcia PILM AAML 39 213 0 15 Jul 2020
Certifying Decision Trees Against Evasion Attacks by Program Analysis Stefano Calzavara Pietro Ferrara Claudio Lucchese AAML 21 10 0 06 Jul 2020
A Survey of Machine Learning Methods and Challenges for Windows Malware Classification Edward Raff Charles K. Nicholas AAML 29 54 0 15 Jun 2020
Adversarial Attack on Hierarchical Graph Pooling Neural Networks Haoteng Tang Guixiang Ma Yurong Chen Lei Guo Wei Wang Bo Zeng Liang Zhan AAML 29 28 0 23 May 2020
Encryption Inspired Adversarial Defense for Visual Classification Maungmaung Aprilpyone Hitoshi Kiya 16 32 0 16 May 2020