ROOM, a novel Real-time Online-Offline attack construction Model where an offline component serves to warm up the online algorithm, making it possible to generate highly successful attacks under time constraints.
A Pytorch code for our paper: ROOM: Adversarial Machine Learning Attacks Under Real-Time Constraints.
If you find this code useful in your research, please cite:
@misc{https://doi.org/10.48550/arxiv.2201.01621,
doi = {10.48550/ARXIV.2201.01621},
url = {https://arxiv.org/abs/2201.01621},
author = {Guesmi, Amira and Khasawneh, Khaled N. and Abu-Ghazaleh, Nael and Alouani, Ihsen},
keywords = {Cryptography and Security (cs.CR), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {ROOM: Adversarial Machine Learning Attacks Under Real-Time Constraints},
publisher = {arXiv},
year = {2022},
copyright = {arXiv.org perpetual, non-exclusive license}
}