IEEE European Symposium on Security and Privacy

IEEE EuroS&P 2022 - Papers on Adversarial Machine Learning

Topics · Papers

Adversarial Machine Learning

aaeCAPTCHA: The Design and Implementation of Audio Adversarial CAPTCHA
Md Imran Hossen (University of Louisiana at Lafayette), Xiali Hei (University of Louisiana at Lafayette)
[Paper]
[Artifact]
Captcha me if you can: Imitation Games with Reinforcement Learning
Ilias Tsingenopoulos (imec-DistriNet, KU Leuven), Davy Preuveneers (imec-DistriNet, KU Leuven), Lieven Desmet (imec-DistriNet, KU Leuven), Wouter Joosen (imec-DistriNet, KU Leuven)
[Artifact]
Dynamic Backdoor Attacks Against Machine Learning Models
Ahmed Salem (Microsoft Research), Rui Wen (CISPA Helmholtz Center for Information Security), Michael Backes (CISPA Helmholtz Center for Information Security), Shiqing Ma (Rutgers University), Yang Zhang (CISPA Helmholtz Center for Information Security)
[Paper]
[Artifact]
GRAPHITE: Generating Automatic Physical Examples for Machine-Learning Attacks on Computer Vision Systems
Ryan Feng (University of Michigan), Neal Mangaokar (University of Michigan), Jiefeng Chen (University of Wisconsin), Earlence Fernandes (University of Wisconsin), Somesh Jha (University of Wisconsin), Atul Prakash (University of Michigan)
[Paper]
[Artifact]
Towards Fair and Robust Classification
Haipei Sun (Stevens Institute of Technology), Kun Wu (Stevens Institute of Technology), Ting Wang (Pennsylvania State University), Wendy Hui Wang (Stevens Institute of Technology)
[Artifact]
TrojanZoo: Towards Unified, Holistic, and Practical Evaluation of Neural Backdoors
Ren Pang (Pennsylvania State University), Zheng Zhang (Northwestern Univeristy), Xiangshan Gao (Zhejiang University), Zhaohan Xi (Pennsylvania State University), Shouling Ji (Zhejiang University), Peng Cheng (Zhejiang University), Xiapu Luo (The Hong Kong Polytechnic University), Ting Wang (Pennsylvania State University)
[Paper]
[Artifact]