Steganalysis of JPEG images using non-linear residuals

Autor: Chao XIA, Yaqi LIU, Qingxiao GUAN, Xin JIN, Yanshuo ZHANG, Shengwei XU
Jazyk: čínština
Rok vydání: 2023
Předmět:
Zdroj: Tongxin xuebao, Vol 44, Pp 142-152 (2023)
Druh dokumentu: article
ISSN: 1000-436X
DOI: 10.11959/j.issn.1000-436x.2023010
Popis: Most current JPEG steganalytic methods can only extract features from a series of linear residuals.Non-linear filters are not considered in these JPEG steganalytic methods, resulting in single types of residuals.Hence, a JPEG steganalytic method using non-linear residuals was proposed.Firstly, non-linear residuals were generated without a high computational cost by using element-wise minimum and maximum operations across a couple of linear residuals which had been obtained in the current JPEG steganalytic method.Secondly, according to the JPEG phase, the non-linear residual was divided into sub-residuals in which the histogram features were extracted.Thirdly, considering the minimum and maximum operators, the symmetrization method was accordingly designed.Finally, all the symmetrized histogram features were concatenated to form the final feature set.Experimental results indicate that the performance for JPEG steganalysis can be improved effectively by using both the linear and the non-linear residuals.
Databáze: Directory of Open Access Journals