@Article{cmc.2020.09784,
AUTHOR = {Junxiang Wang, Lin Huang, Ying Zhang, Yonghong Zhu, Jiangqun Ni, Yunqing Shi},
TITLE = {An Effective Steganalysis Algorithm for Histogram-Shifting Based Reversible Data Hiding},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {64},
YEAR = {2020},
NUMBER = {1},
PAGES = {325--344},
URL = {http://www.techscience.com/cmc/v64n1/39145},
ISSN = {1546-2226},
ABSTRACT = {To measure the security for hot searched reversible data hiding (RDH) 
technique, especially for the common-used histogram-shifting based RDH (denoted as 
HS-RDH), several steganalysis schemes are designed to detect whether some secret data 
has been hidden in a normal-looking image. However, conventional steganalysis schemes 
focused on the previous RDH algorithms, i.e., some early spatial/pixel domain-based 
histogram-shifting (HS) schemes, which might cause great changes in statistical 
characteristics and thus be easy to be detected. For recent improved methods, such as 
some adaptive prediction error (PE) based embedding schemes, those conventional 
schemes might be invalid, since those adaptive embedding mechanism would effectively 
reduce the embedding trace and thus increase the difficulty of steganalysis. Therefore, a 
novel steganalysis method is proposed in this paper to detect recent adaptive RDH 
schemes and provide a more effective detection tool for RDH. The contributions of this 
paper could be summarized as follows. (1) By analyzing the characteristics for those 
adaptive HS-RDH, an effective “flat ground” based detection method is designed to fast 
identify whether the given image is used to hide secret data; (2) According to the 
empirical statistical model, double check mechanism is provided to improve the detection 
accuracy; (3) In addition, to further improve detection ability, some detailed information 
for secret data, i.e., its content and embedding location are further estimated. Compared 
with conventional steganalysis methods, experimental results indicate that our proposed 
algorithm could achieve a better detection accuracy and meanwhile acquire more detailed 
information on secret data.},
DOI = {10.32604/cmc.2020.09784}
}