A Protection Method of Trained CNN Model Using Feature Maps Transformed With Secret Key From Unauthorized Access

• URL: http://arxiv.org/abs/2109.00224v1
• Date: Wed, 1 Sep 2021 07:47:05 GMT
• Title: A Protection Method of Trained CNN Model Using Feature Maps Transformed With Secret Key From Unauthorized Access
• Authors: MaungMaung AprilPyone and Hitoshi Kiya
• Abstract summary: We propose a model protection method for convolutional neural networks (CNNs) with a secret key. The proposed method applies a block-wise transformation with a secret key to feature maps in the network.
• Score: 15.483078145498085
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we propose a model protection method for convolutional neural networks (CNNs) with a secret key so that authorized users get a high classification accuracy, and unauthorized users get a low classification accuracy. The proposed method applies a block-wise transformation with a secret key to feature maps in the network. Conventional key-based model protection methods cannot maintain a high accuracy when a large key space is selected. In contrast, the proposed method not only maintains almost the same accuracy as non-protected accuracy, but also has a larger key space. Experiments were carried out on the CIFAR-10 dataset, and results show that the proposed model protection method outperformed the previous key-based model protection methods in terms of classification accuracy, key space, and robustness against key estimation attacks and fine-tuning attacks.

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