Moiré pattern generation-based image steganography

doi:10.1016/j.jisa.2024.103753

Moiré pattern generation-based image steganography

2024-05-01

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AI

DOI：10.1016/j.jisa.2024.103753

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Abstract

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Generative steganography has developed recently due to its high resistance against steganalysis detection. It usually synthesizes stego images directly from secret information. In contrast to this manner, we propose a generative steganographic scheme by synthesizing Moir & eacute; patterns in this paper. Moir & eacute; patterns are widely observed in captured photos. They present various shapes, colors, and frequency ranges, which are expected to help carry secret information robustly and securely. The scheme synthesizes Moir & eacute; patterns via a Moir & eacute; pattern generator. Then a secret message is encoded in these patterns by a parallel encoder. The Moir & eacute; pattern generator employs a multi-branch structure to generate sub Moir & eacute; patterns at distinct frequencies. A discriminator is further imposed to ensure the realness of synthesized Moir & eacute; patterns. The parallel encoder spreads secret information over Moir & eacute; patterns in both frequency and spatial domain. A decoder and a steganalyzer are also included to ensure the robustness and undetectability of the information hiding. Furthermore, a two-stage training strategy is designed to accomplish both Moir & eacute; pattern generation and information hiding tasks. Experimental results demonstrate that the proposed scheme presents high undetectability against existing steganalytic tools, meanwhile, it can resist common image attacks such as AWGN and JPEG compression.

Keywords:

Generative steganography

Moir & eacute

pattern

Deep learning

Robustness

Undetectability

Moiré pattern generation-based image steganography

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