Summary
International Workshop on Smart Info-Media Systems in Asia
2021
Session Number:RS1
Session:
Number:RS1-2
Protecting Semantic Segmentation Models by Using Block-Wise Image Encryption with Secret Key from Unauthorized Access
Hiroki Ito, MaungMaung AprilPyone, Hitoshi Kiya,
pp.22-27
Publication Date:2021/9/20
Online ISSN:2188-5079
DOI:10.34385/proc.66.RS1-2
PDF download (3.3MB)
Summary:
Since production-level trained deep neural networks (DNNs) are of a great business value, protecting such DNN models against copyright infringement and unauthorized access is in a rising demand. However, conventional model protection methods focused only the image classification task, and these protection methods were never applied to semantic segmentation although it has an increasing number of applications. In this paper, we propose to protect semantic segmentation models from unauthorized access by utilizing block-wise transformation with a secret key for the first time. Protected models are trained by using transformed images. Experiment results show that the proposed protection method allows rightful users with the correct key to access the model to full capacity and deteriorate the performance for unauthorized users. However, protected models slightly drop the segmentation performance compared to non-protected models.