Active steganalysis for histogram-shifting based reversible data hiding

2012 ◽  
Vol 285 (10-11) ◽  
pp. 2510-2518 ◽  
Author(s):  
Der-Chyuan Lou ◽  
Chao-Lung Chou ◽  
Hao-Kuan Tso ◽  
Chung-Cheng Chiu
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Histogram Shifting ◽  
Active Steganalysis

scholarly journals Generalized Reversible Data Hiding with Content-Adaptive Operation and Fast Histogram Shifting Optimization

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 917
Author(s):  
Limengnan Zhou ◽  
Hongyu Han ◽  
Hanzhou Wu
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Hot Spot ◽  
Data Embedding ◽  
Histogram Shifting ◽  
Secret Data ◽  
Content Selection ◽  
Wide Range ◽  
Map Generation ◽  
Content Adaptive

Reversible data hiding (RDH) has become a hot spot in recent years as it allows both the secret data and the raw host to be perfectly reconstructed, which is quite desirable in sensitive applications requiring no degradation of the host. A lot of RDH algorithms have been designed by a sophisticated empirical way. It is not easy to extend them to a general case, which, to a certain extent, may have limited their wide-range applicability. Therefore, it motivates us to revisit the conventional RDH algorithms and present a general framework of RDH in this paper. The proposed framework divides the system design of RDH at the data hider side into four important parts, i.e., binary-map generation, content prediction, content selection, and data embedding, so that the data hider can easily design and implement, as well as improve, an RDH system. For each part, we introduce content-adaptive techniques that can benefit the subsequent data-embedding procedure. We also analyze the relationships between these four parts and present different perspectives. In addition, we introduce a fast histogram shifting optimization (FastHiSO) algorithm for data embedding to keep the payload-distortion performance sufficient while reducing the computational complexity. Two RDH algorithms are presented to show the efficiency and applicability of the proposed framework. It is expected that the proposed framework can benefit the design of an RDH system, and the introduced techniques can be incorporated into the design of advanced RDH algorithms.

scholarly journals An Effective Steganalysis Algorithm for Histogram-shifting Based Reversible Data Hiding

2020 ◽  
Vol 64 (1) ◽  
pp. 325-344
Author(s):  
Junxiang Wang ◽  
Lin Huang ◽  
Ying Zhang ◽  
Yonghong Zhu ◽  
Jiangqun Ni ◽  
...  
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Histogram Shifting

Reversible Data Hiding for Btc-compressed Images Based on Bitplane Flipping and Histogram Shifting of Mean Tables

2011 ◽  
Vol 10 (7) ◽  
pp. 1421-1426 ◽  
Author(s):  
Cai-Hua Li ◽  
Zhe-Ming Lu ◽  
Yu-Xin Su
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Histogram Shifting ◽  
Compressed Images

A high capacity reversible data hiding scheme for encrypted covers based on histogram shifting

2019 ◽  
Vol 47 ◽  
pp. 199-207 ◽  
Author(s):  
Ru Zhang ◽  
Chunjing Lu ◽  
Jianyi Liu
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Histogram Shifting

Reversible data hiding based on RSBEMD coding and adaptive multi-segment left and right histogram shifting

2020 ◽  
Vol 81 ◽  
pp. 115715 ◽  
Author(s):  
Fei Peng ◽  
Yu Zhao ◽  
Xiang Zhang ◽  
Min Long ◽  
Wei-qiang Pan
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Histogram Shifting ◽  
Left And Right
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