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Titlebook: Information Hiding; 13th International C Tomá? Filler,Tomá? Pevny,Andrew Ker Conference proceedings 2011 Springer-Verlag GmbH Berlin Heidel

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樓主: ARRAY
41#
發(fā)表于 2025-3-28 15:48:45 | 只看該作者
42#
發(fā)表于 2025-3-28 21:55:24 | 只看該作者
43#
發(fā)表于 2025-3-29 00:54:18 | 只看該作者
Breaking HUGO – The Process Discoverybreaking HUGO – one of the most advanced steganographic systems ever published. We believe that researchers working in steganalysis of digital media and related fields will find it interesting, inspiring, and perhaps even entertaining to read about the details of our journey, including the dead ends
44#
發(fā)表于 2025-3-29 03:10:04 | 只看該作者
Steganalysis of Content-Adaptive Steganography in Spatial Domains. When combined with advanced coding techniques, adaptive steganographic methods can embed rather large payloads with low statistical detectability at least when measured using feature-based steganalyzers trained on a given cover source. The recently proposed steganographic algorithm HUGO is an exa
45#
發(fā)表于 2025-3-29 08:05:41 | 只看該作者
46#
發(fā)表于 2025-3-29 11:35:19 | 只看該作者
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發(fā)表于 2025-3-29 17:59:14 | 只看該作者
48#
發(fā)表于 2025-3-29 23:22:30 | 只看該作者
Video Steganography with Perturbed Motion Estimationmed domain of images or raw videos which are vulnerable to certain existing steganalyzers, our approach targets the internal dynamics of video compression. Inspired by Fridrich et al’s perturbed quantization (PQ) steganography, a technique called perturbed motion estimation (PME) is introduced to pe
49#
發(fā)表于 2025-3-30 03:14:27 | 只看該作者
Soft-SCS: Improving the Security and Robustness of the Scalar-Costa-Scheme by Optimal Distribution Me AWGN channel. After recalling the principle of SCS we highlight its secure implementations regarding the Watermarked contents Only Attack, and we also describe the relations between the alphabet size and the secure embedding parameters. Since the gap between the achievable rates of secure-SCS and
50#
發(fā)表于 2025-3-30 04:21:47 | 只看該作者
Improving Tonality Measures for Audio Watermarking of the ear. The performances of such models in audio watermarking applications are tightly related to the determination of tonal and noise-like components. In this paper, we present an improved tonality estimation and its integration into a psychoacoustic model. Instead of conventional binary class
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