计算机科学
有损压缩
稳健性(进化)
隐写术
计算机工程
实时计算
计算机网络
嵌入
人工智能
生物化学
基因
化学
作者
Ye Yao,Liang Huang,Hui Wang,Qi Chang,Yizhi Ren,Fengjun Xiao
标识
DOI:10.1109/tmm.2023.3334487
摘要
With the increasing popularity of Online Social Networks (OSNs), covert communication is rapidly shifting from lossless channels like email to lossy channels, specifically social networks. In response to this trend, robust adaptive steganography has emerged as a powerful technique for concealing information in lossy transport channels. Previous approaches have aimed to address the challenge of JPEG image compression during transmission by utilizing static compression-resistant domains, Syndrome-Trellis Codes (STC), and Error Correction Codes (ECC). However, reliance on a significant number of ECC check codes to ensure robustness could inadvertently affect security. In response to this challenge, we introduce the “Adaptive STC-ECC” strategy, which enhances security by minimizing the number of check codes without compromising robustness. We further improve the robustness by simulating the embedding process and strategically placing the wet point in unstable cover elements. Furthermore, we exploit the residual information between the pre-cover and cover images to adjust the distortion and accurately determine the direction of the dither modulation, thus improving the overall security. Extensive experiments have been conducted to evaluate the performance of our proposed approach, and the results demonstrate its superior robustness and security compared to existing state-of-the-art approaches.
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