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Keywords = chaotic hiding and anti-hiding

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18 pages, 16091 KiB  
Article
Study of Generalized Chaotic Synchronization Method Incorporating Error-Feedback Coefficients
by Yanan Xing, Wenjie Dong, Jian Zeng, Pengteng Guo, Jing Zhang and Qun Ding
Entropy 2023, 25(5), 818; https://doi.org/10.3390/e25050818 - 18 May 2023
Cited by 5 | Viewed by 1815
Abstract
In this paper, taking the generalized synchronization problem of discrete chaotic systems as a starting point, a generalized synchronization method incorporating error-feedback coefficients into the controller based on the generalized chaos synchronization theory and stability theorem for nonlinear systems is proposed. Two discrete [...] Read more.
In this paper, taking the generalized synchronization problem of discrete chaotic systems as a starting point, a generalized synchronization method incorporating error-feedback coefficients into the controller based on the generalized chaos synchronization theory and stability theorem for nonlinear systems is proposed. Two discrete chaotic systems with different dimensions are constructed in this paper, the dynamics of the proposed systems are analyzed, and finally, the phase diagrams, Lyapunov exponent diagrams, and bifurcation diagrams of these are shown and described. The experimental results show that the design of the adaptive generalized synchronization system is achievable in cases in which the error-feedback coefficient satisfies certain conditions. Finally, a chaotic hiding image encryption transmission system based on a generalized synchronization approach is proposed, in which an error-feedback coefficient is introduced into the controller. Full article
(This article belongs to the Topic Advances in Nonlinear Dynamics: Methods and Applications)
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21 pages, 8000 KiB  
Article
A Multi-Domain Embedding Framework for Robust Reversible Data Hiding Scheme in Encrypted Videos
by Pei Chen, Zhuo Zhang, Yang Lei, Ke Niu and Xiaoyuan Yang
Electronics 2022, 11(16), 2552; https://doi.org/10.3390/electronics11162552 - 15 Aug 2022
Cited by 3 | Viewed by 1995
Abstract
For easier cloud management, reversible data hiding is performed in an encrypted domain to embed label information. However, the existing schemes are not robust and may cause the loss of label information during transmission. Enhancing robustness while maintaining reversibility in data hiding is [...] Read more.
For easier cloud management, reversible data hiding is performed in an encrypted domain to embed label information. However, the existing schemes are not robust and may cause the loss of label information during transmission. Enhancing robustness while maintaining reversibility in data hiding is a challenge. In this paper, a multi-domain embedding framework in encrypted videos is proposed to achieve both robustness and reversibility. In the framework, the multi-domain characteristic of encrypted video is fully used. The element for robust embedding is encrypted through Logistic chaotic scrambling, which is marked as element-I. To further improve robustness, the label information will be encoded with the Bose–Chaudhuri–Hocquenghem code. Then, the label information will be robustly embedded into element-I by modulating the amplitude of element-I, in which the auxiliary information is generated for lossless recovery of the element-I. The element for reversible embedding is marked as element-II, the sign of which will be encrypted by stream cipher. The auxiliary information will be reversibly embedded into element-Ⅱ through traditional histogram shifting. To verity the feasibility of the framework, an anti-recompression RDH-EV based on the framework is proposed. The experimental results show that the proposed scheme outperforms the current representative ones in terms of robustness, while achieving reversibility. In the proposed scheme, video encryption and data hiding are commutative and the original video bitstream can be recovered fully. These demonstrate the feasibility of the multi-domain embedding framework in encrypted videos. Full article
(This article belongs to the Topic Computer Vision and Image Processing)
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