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Enhancing Image Steganography via Stego Generation and Selection

Citation Author(s):
Minglin Liu, Weiqi Luo, Peijia Zheng
Submitted by:
Tingting Song
Last updated:
16 June 2021 - 3:56am
Document Type:
Presentation Slides
Document Year:

Abstract 

Abstract: 

Unlike most existing steganography methods which are main- ly focused on designing embedding cost, in this paper, we propose a new method to enhance existing steganographic methods via stego generation and selection. The proposed method firstly trains a steganalytic network according to the steganography to be enhanced, and then tries to adjust a tiny part of original embedding costs based on the magnitudes of it and the corresponding gradients obtained from the pre-trained network, and generates many candidate stegos in a random manner. Finally, the method selects a stego according to its image residual distance to cover. Extensive experimental re- sults have shown that the proposed method can siginficantly enhance the security performance of current steganography in spatial domain against four steganalytic classifiers. In ad- dition, comparative analysis between original stegos and the resulting ones with the proposed method are given.

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