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Enhancing JPEG Steganography using Iterative Adversarial Examples
[article]
2019
arXiv
pre-print
Convolutional Neural Networks (CNN) based methods have significantly improved the performance of image steganalysis compared with conventional ones based on hand-crafted features. However, many existing literatures on computer vision have pointed out that those effective CNN-based methods can be easily fooled by adversarial examples. In this paper, we propose a novel steganography framework based on adversarial example in an iterative manner. The proposed framework first starts from an existing
arXiv:1909.07556v3
fatcat:5zmv3pefijgptmcdupmmpptfua