ABSTRACT In this work, we propose a new adaptive chaotic steganographic method based on the Discrete Cosine Transform (DCT) and a reversible mapping function. The mapping function is used to map the secret bits into their corresponding symbols. This mapping technique has to preserve the same dynamics, properties and distribution of the original DCT coefficients. The novelty of our approach is based on the adaptive selection phase of embedding spots. This selection is established through a blindness condition which is applied over each image of the database. The proposed embedding scheme within the middle DCT coefficients shows lower probability of detection and higher flexibility in extraction. We evaluate the detection of our method using the Ensemble Classifiers and a set of frequency and spatial domain feature extractors such as the Spatial domain Rich Model (SRM) features, Chen et al.'s 486-dimensional both inter- and intra-block Markov-based features and Liu's 216-dimensional adaptive steganography-based features.

中文翻译：

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USAD：DCT 域中不可检测的隐写方法

摘要 在这项工作中，我们提出了一种基于离散余弦变换 (DCT) 和可逆映射函数的新的自适应混沌隐写方法。映射函数用于将秘密位映射到它们对应的符号中。这种映射技术必须保留原始 DCT 系数的相同动态、特性和分布。我们方法的新颖性基于嵌入点的自适应选择阶段。这种选择是通过应用在数据库的每个图像上的失明条件建立的。在中间 DCT 系数中提出的嵌入方案显示出较低的检测概率和较高的提取灵活性。