Making Acoustic Side-Channel Attacks on Noisy Keyboards Viable with LLM-Assisted Spectrograms' "Typo" Correction
Paper • 2504.11622 • Published
How to use seyyedaliayati/zoom_model with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("seyyedaliayati/zoom_model", dtype="auto")How to use seyyedaliayati/zoom_model with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for seyyedaliayati/zoom_model to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for seyyedaliayati/zoom_model to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for seyyedaliayati/zoom_model to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="seyyedaliayati/zoom_model",
max_seq_length=2048,
)This is a fine-tuned version of the LLaMA-3.2-3B model for Acoustic Side-Channel Attacks (ASCA), designed to improve keystroke classification and error correction in noisy environments. The model leverages Vision Transformers (VTs) for spectrogram classification and Large Language Models (LLMs) for typo correction.
If you use this model, please cite the following paper:
@article{ayati2025making,
title={Making Acoustic Side-Channel Attacks on Noisy Keyboards Viable with LLM-Assisted Spectrograms' "Typo" Correction},
author={Ayati, Seyyed Ali and Park, Jin Hyun and Cai, Yichen and Botacin, Marcus},
journal={arXiv preprint arXiv:2504.11622},
year={2025},
url={https://arxiv.org/abs/2504.11622}
}