@inproceedings{7024e9ff938f49e183e39132e5a88750,
title = "An Effective Neural Network Model Protection Method Against Model Stealing Attacks for Image Classification Applications",
abstract = "The growing adoption of Deep Learning (DL) models at the network edge necessitates robust security measures. Image preprocessing, a common technique for securing DL models, often involves shuffling the pixels of training images before feeding them to the model. In this work, we found that the shuffle-then-flip method offers superior resilience compared to the shuffle-only method. We also investigate the effectiveness of the shuffle-then-flip preprocessing technique in enhancing the security of models against attacks.",
author = "Chiou, \{Lih Yih\} and Lee, \{Yu Hung\} and Chiu, \{Chung Chieh\} and Hsu, \{Shun Hsiu\}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 21st International System-on-Chip Design Conference, ISOCC 2024 ; Conference date: 19-08-2024 Through 22-08-2024",
year = "2024",
doi = "10.1109/ISOCC62682.2024.10761995",
language = "English",
series = "Proceedings - International SoC Design Conference 2024, ISOCC 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "125--126",
booktitle = "Proceedings - International SoC Design Conference 2024, ISOCC 2024",
address = "United States",
}