Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning

14 May 2020

Yan Zheng

Yang Liu

Papers citing "Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning"

21 / 21 papers shown

Title
How vulnerable is my policy? Adversarial attacks on modern behavior cloning policies Basavasagar Patil Akansha Kalra Guanhong Tao Daniel S. Brown AAML 76 0 0 06 Feb 2025
UNIDOOR: A Universal Framework for Action-Level Backdoor Attacks in Deep Reinforcement Learning Oubo Ma L. Du Yang Dai Chunyi Zhou Qingming Li Yuwen Pu Shouling Ji 46 0 0 28 Jan 2025
Adversarial Attacks on Reinforcement Learning Agents for Command and Control Ahaan Dabholkar James Z. Hare Mark R. Mittrick John Richardson Nick Waytowich Priya Narayanan Saurabh Bagchi AAML 37 1 0 02 May 2024
PGN: A perturbation generation network against deep reinforcement learning Xiangjuan Li Feifan Li Yang Li Quanbiao Pan AAML 27 2 0 20 Dec 2023
Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attacks Mohammad Mohammadi Jonathan Nöther Debmalya Mandal Adish Singla Goran Radanović AAML OffRL 35 9 0 27 Feb 2023
Regret-Based Defense in Adversarial Reinforcement Learning Roman Belaire Pradeep Varakantham Thanh Nguyen David Lo AAML 23 3 0 14 Feb 2023
SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning Maxwell Standen Junae Kim Claudia Szabo AAML 35 5 0 11 Jan 2023
New Challenges in Reinforcement Learning: A Survey of Security and Privacy Yunjiao Lei Dayong Ye Sheng Shen Yulei Sui Tianqing Zhu Wanlei Zhou 33 18 0 31 Dec 2022
A Survey on Reinforcement Learning Security with Application to Autonomous Driving Ambra Demontis Maura Pintor Luca Demetrio Kathrin Grosse Hsiao-Ying Lin Chengfang Fang Battista Biggio Fabio Roli AAML 42 4 0 12 Dec 2022
Imitating Opponent to Win: Adversarial Policy Imitation Learning in Two-player Competitive Games Viet The Bui Tien Mai T. Nguyen AAML 33 5 0 30 Oct 2022
A Transferable and Automatic Tuning of Deep Reinforcement Learning for Cost Effective Phishing Detection Orel Lavie A. Shabtai Gilad Katz AAML OffRL 30 1 0 19 Sep 2022
Ad Hoc Teamwork in the Presence of Adversaries Ted Fujimoto Samrat Chatterjee A. Ganguly 30 2 0 09 Aug 2022
RoMFAC: A robust mean-field actor-critic reinforcement learning against adversarial perturbations on states Ziyuan Zhou Guanjun Liu AAML 35 23 0 15 May 2022
Deep-Attack over the Deep Reinforcement Learning Yang Li Quanbiao Pan Min Zhang AAML 19 13 0 02 May 2022
Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual Patterns Prasanth Buddareddygari Travis Zhang Yezhou Yang Yi Ren AAML 37 13 0 16 Sep 2021
Defending Against Backdoor Attacks in Natural Language Generation Xiaofei Sun Xiaoya Li Yuxian Meng Xiang Ao Fei Wu Jiwei Li Tianwei Zhang AAML SILM 31 47 0 03 Jun 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
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
Deep Reinforcement Learning for Cyber Security Thanh Thi Nguyen Vijay Janapa Reddi OffRL AI4CE 10 313 0 13 Jun 2019
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 245 915 0 21 Apr 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,842 0 08 Jul 2016