基于动态分配区间的轮盘赌生成语言隐写

IF 7.2 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Yihao Wang , Ruiqi Song, Lingxiao Li , Ru Zhang, Jianyi Liu
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引用次数: 0

摘要

现有的语言隐写方案往往忽略候选池中标记的条件概率,将一个编码分配给所有标记,从而导致相同的选择可能性。这种方法导致选择低cp令牌,降低了stegos的质量,使它们更容易被检测到。本文提出了一种基于分配区间的DAIRstega算法。DAIRstega首先使用读取密钥的一部分来构建轮盘赌区域。然后,该方案利用轮盘赌的思想,以令牌的cp值作为分配轮盘赌区域(即区间长度)的主要依据。因此,具有较大cp的令牌被分配更多的区域。在分配过程中,我们设计了一些分配函数和三个约束来优化分配过程。此外,DAIRstega支持基于提示的可控stegos生成。丰富的实验表明,所提出的嵌入方式和DAIRstega比现有的嵌入方式和基线具有更好的性能,表现出较强的感知、统计和语义隐藏性,以及抗隐写分析能力。它还可以生成高质量的更长的stegos,解决了这项任务的不足。DAIRstega被证实具有作为安全水印的潜力,为其发展提供了见解。我们的代码和数据可在:https://github.com/WangYH-BUPT/DAIRstega。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamically allocated interval-based generative linguistic steganography with roulette wheel
Existing linguistic steganography schemes often overlook the conditional probability (CP) of tokens in the candidate pool, allocating the one coding to all tokens, which results in identical selection likelihoods. This approach leads to the selection of low-CP tokens, degrading the quality of stegos and making them more detectable. This paper proposes a scheme based on the interval allocated, called DAIRstega. DAIRstega first uses a portion of the read secret to build the roulette area. Then, this scheme uses the idea of the roulette wheel and takes the CPs of tokens as the main basis for allocating the roulette area (i.e., the interval length). Thus, tokens with larger CPs are allocated more area. The secret will have an increased likelihood of selecting a token with a higher CP. During allocation, we design some allocation functions and three constraints to optimize the process. Additionally, DAIRstega supports prompt-based controllable generation of stegos. Rich experiments show that the proposed embedding way and DAIRstega perform better than the existing ways and baselines, which shows strong perceptual, statistical, and semantic concealment, as well as anti-steganalysis ability. It can also generate high-quality longer stegos, addressing the deficiencies in this task. DAIRstega is confirmed to have potential as a secure watermarking, offering insights for its development. Our codes and data are available at: https://github.com/WangYH-BUPT/DAIRstega.
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来源期刊
Applied Soft Computing
Applied Soft Computing 工程技术-计算机:跨学科应用
CiteScore
15.80
自引率
6.90%
发文量
874
审稿时长
10.9 months
期刊介绍: Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities. Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.
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