Training DNN Model with Secret Key for Model Protection
Machine Learning
2020-08-07 v1 Cryptography and Security
Machine Learning
Abstract
In this paper, we propose a model protection method by using block-wise pixel shuffling with a secret key as a preprocessing technique to input images for the first time. The protected model is built by training with such preprocessed images. Experiment results show that the performance of the protected model is close to that of non-protected models when the key is correct, while the accuracy is severely dropped when an incorrect key is given, and the proposed model protection is robust against not only brute-force attacks but also fine-tuning attacks, while maintaining almost the same performance accuracy as that of using a non-protected model.
Cite
@article{arxiv.2008.02450,
title = {Training DNN Model with Secret Key for Model Protection},
author = {MaungMaung AprilPyone and Hitoshi Kiya},
journal= {arXiv preprint arXiv:2008.02450},
year = {2020}
}
Comments
to appear in 2020 IEEE 9th Global Conference on Consumer Electronics (GCCE 2020)