Adversarial Attacks on Neural Network Policies

8 February 2017

Sandy Huang

Pieter Abbeel

Papers citing "Adversarial Attacks on Neural Network Policies"

50 / 184 papers shown

Title
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary Huan Zhang Hongge Chen Duane S. Boning Cho-Jui Hsieh 67 163 0 21 Jan 2021
Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data F. Cartella Orlando Anunciação Yuki Funabiki D. Yamaguchi Toru Akishita Olivier Elshocht AAML 65 71 0 20 Jan 2021
Limitations of Deep Neural Networks: a discussion of G. Marcus' critical appraisal of deep learning Stefanos Tsimenidis 25 12 0 22 Dec 2020
Invisible Perturbations: Physical Adversarial Examples Exploiting the Rolling Shutter Effect Athena Sayles Ashish Hooda M. Gupta Rahul Chatterjee Earlence Fernandes AAML 22 76 0 26 Nov 2020
Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks Amin Rakhsha Goran Radanović R. Devidze Xiaojin Zhu Adish Singla AAML OffRL 30 29 0 21 Nov 2020
Fault-Aware Robust Control via Adversarial Reinforcement Learning Fan Yang Chao Yang Di Guo Huaping Liu F. Sun 42 4 0 17 Nov 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks Tao Bai Jinqi Luo Jun Zhao AAML 51 8 0 03 Nov 2020
One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL Saurabh Kumar Aviral Kumar Sergey Levine Chelsea Finn OffRL 16 90 0 27 Oct 2020
Online Safety Assurance for Deep Reinforcement Learning Noga H. Rotman Michael Schapira Aviv Tamar OffRL 38 5 0 07 Oct 2020
Machine Learning in Event-Triggered Control: Recent Advances and Open Issues Leila Sedghi Zohaib Ijaz Md. Noor-A.-Rahim K. Witheephanich Dirk Pesch AI4CE 36 15 0 27 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 46 62 0 11 Sep 2020
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics Yanchao Sun Da Huo Furong Huang AAML OffRL OnRL 34 49 0 02 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 32 73 0 07 Aug 2020
Robust Deep Reinforcement Learning through Adversarial Loss Tuomas P. Oikarinen Wang Zhang Alexandre Megretski Luca Daniel Tsui-Wei Weng AAML 49 94 0 05 Aug 2020
Adversarial jamming attacks and defense strategies via adaptive deep reinforcement learning Feng Wang Chen Zhong M. C. Gursoy Senem Velipasalar AAML 23 8 0 12 Jul 2020
Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey Arun Das P. Rad XAI 42 593 0 16 Jun 2020
Stealing Deep Reinforcement Learning Models for Fun and Profit Kangjie Chen Shangwei Guo Tianwei Zhang Xiaofei Xie Yang Liu MLAU MIACV OffRL 24 45 0 09 Jun 2020
Robust Reinforcement Learning with Wasserstein Constraint Linfang Hou Liang Pang Xin Hong Yanyan Lan Zhiming Ma Dawei Yin 27 24 0 01 Jun 2020
Adversarial Attacks on Reinforcement Learning based Energy Management Systems of Extended Range Electric Delivery Vehicles Pengyue Wang Yuante Li Shashi Shekhar W. Northrop AAML 21 8 0 01 Jun 2020
Few-Shot Open-Set Recognition using Meta-Learning Bo Liu Hao Kang Haoxiang Li G. Hua Nuno Vasconcelos BDL EDL 28 89 0 27 May 2020
Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning Michael Everett Bjorn Lutjens Jonathan P. How AAML 20 41 0 11 Apr 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 16 121 0 28 Mar 2020
Adaptive Reward-Poisoning Attacks against Reinforcement Learning Xuezhou Zhang Yuzhe Ma Adish Singla Xiaojin Zhu AAML 29 124 0 27 Mar 2020
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations Huan Zhang Hongge Chen Chaowei Xiao Bo Li Mingyan D. Liu Duane S. Boning Cho-Jui Hsieh AAML 49 261 0 19 Mar 2020
Generating Socially Acceptable Perturbations for Efficient Evaluation of Autonomous Vehicles Songan Zhang H. Peng S. Nageshrao E. Tseng AAML 27 5 0 18 Mar 2020
Stop-and-Go: Exploring Backdoor Attacks on Deep Reinforcement Learning-based Traffic Congestion Control Systems Yue Wang Esha Sarkar Wenqing Li Michail Maniatakos Saif Eddin Jabari AAML 31 60 0 17 Mar 2020
On the Robustness of Cooperative Multi-Agent Reinforcement Learning Jieyu Lin Kristina Dzeparoska Shanghang Zhang A. Leon-Garcia Nicolas Papernot AAML 74 65 0 08 Mar 2020
Enhanced Adversarial Strategically-Timed Attacks against Deep Reinforcement Learning Chao-Han Huck Yang Jun Qi Pin-Yu Chen Ouyang Yi I-Te Danny Hung Chin-Hui Lee Xiaoli Ma AAML 21 29 0 20 Feb 2020
When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions Y. Sagduyu Yi Shi T. Erpek William C. Headley Bryse Flowers G. Stantchev Zhuo Lu AAML 20 39 0 24 Jan 2020
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 21 104 0 13 Nov 2019
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 58 101 0 16 Oct 2019
Policy Poisoning in Batch Reinforcement Learning and Control Yuzhe Ma Xuezhou Zhang Wen Sun Xiaojin Zhu AAML OffRL 21 109 0 13 Oct 2019
SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations Ali Dabouei Sobhan Soleymani Fariborz Taherkhani J. Dawson Nasser M. Nasrabadi AAML 104 19 0 08 Oct 2019
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks Tianyu Pang Kun Xu Jun Zhu AAML 28 103 0 25 Sep 2019
Say What I Want: Towards the Dark Side of Neural Dialogue Models Haochen Liu Tyler Derr Zitao Liu Jiliang Tang 31 16 0 13 Sep 2019
Density estimation in representation space to predict model uncertainty Tiago Ramalho M. Corbalan UQCV BDL 16 38 0 20 Aug 2019
Deep reinforcement learning in World-Earth system models to discover sustainable management strategies Felix M. Strnad W. Barfuss J. Donges J. Heitzig 30 25 0 15 Aug 2019
Optimal Attacks on Reinforcement Learning Policies Alessio Russo Alexandre Proutiere AAML 27 41 0 31 Jul 2019
Characterizing Attacks on Deep Reinforcement Learning Xinlei Pan Chaowei Xiao Warren He Shuang Yang Jian Peng ... Jinfeng Yi Zijiang Yang Mingyan D. Liu Bo Li D. Song AAML 22 69 0 21 Jul 2019
Learning to Cope with Adversarial Attacks Xian Yeow Lee Aaron J. Havens Girish Chowdhary Soumik Sarkar AAML 38 5 0 28 Jun 2019
Perceptual Based Adversarial Audio Attacks Joseph Szurley J. Zico Kolter AAML 24 25 0 14 Jun 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad Yangqiu Song AAML 30 35 0 09 Jun 2019
Snooping Attacks on Deep Reinforcement Learning Matthew J. Inkawhich Yiran Chen Hai Helen Li AAML 22 25 0 28 May 2019
Adversarial Policies: Attacking Deep Reinforcement Learning Adam Gleave Michael Dennis Cody Wild Neel Kant Sergey Levine Stuart J. Russell AAML 27 349 0 25 May 2019
Testing DNN Image Classifiers for Confusion & Bias Errors Yuchi Tian Ziyuan Zhong Vicente Ordonez Gail E. Kaiser Baishakhi Ray 24 52 0 20 May 2019
Percival: Making In-Browser Perceptual Ad Blocking Practical With Deep Learning Z. Din P. Tigas Samuel T. King B. Livshits VLM 39 29 0 17 May 2019
Data Poisoning Attacks on Stochastic Bandits Fang Liu Ness B. Shroff AAML 23 98 0 16 May 2019
Perceptual Attention-based Predictive Control Keuntaek Lee G. N. An Viacheslav Zakharov Evangelos A. Theodorou 15 19 0 26 Apr 2019
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition Yao Qin Nicholas Carlini Ian Goodfellow G. Cottrell Colin Raffel AAML 38 377 0 22 Mar 2019
Adversarial Out-domain Examples for Generative Models Dario Pasquini Marco Mingione M. Bernaschi WIGM SILM AAML 23 6 0 07 Mar 2019