The development of video steganography has put forward a higher demand for video steganalysis. This paper presents a novel steganalysis against discrete cosine/sine transform (DCT/DST)-based steganography for high efficiency video coding (HEVC) videos. The new steganalysis employs special frames extraction (SFE) and accordion unfolding (AU) transformation to target the latest DCT/DST domain HEVC video steganography algorithms by merging temporal and spatial correlation. In this article, the distortion process of DCT/DST-based HEVC steganography is firstly analyzed. Then, based on the analysis, two kinds of distortion, the intra-frame distortion and the inter-frame distortion, are mainly caused by DCT/DST-based steganography. Finally, to effectively detect these distortions, an innovative method of HEVC steganalysis is proposed, which gives a combination feature of SFE and a temporal to spatial transformation, AU. The experiment results show that the proposed steganalysis performs better than other methods.
Currently, many High Efficiency Video Coding (HEVC) video steganography algorithms based on Intra Prediction Mode (IPM) have been proposed. However, the existing IPM-based video steganalysis algorithms are almost designed for H.264/AVC videos, without considering the unique coding techniques in HEVC, which is the latest video codec standard. Thus, it is of significant value to study IPM-based steganalysis for HEVC videos. In this paper, the general process of IPM-based HEVC steganography is modelled for the first time, and we find that the basic distortion existing in the change of the relationships between each embedded IPM and the adjacent IPMs. By exploiting these weaknesses, we propose a novel IPM steganalysis algorithm based on the Relationship of Adjacent IPMs (RoAIPM) feature. In detail, the RoAIPM is extracted by generating different directional Gray-Level Co-occurrence Matrixes (GLCMs) and texture characteristics of three refilled matrixes: MPM-IPM matrix, Left-IPM matrix and Up-IPM matrix. Experimental results show that, the proposed RoAIPM feature is very sensitive to the little change introduced by IPM-based steganography. Regardless of whether the feature is after 2 dimension reduction or not, in various coding conditions, the proposed steganalysis can both present a well higher detection accuracy against the latest IPM-based HEVC steganography methods and achieve the lowest computational complexity compared with the state-of-the-art works.
Currently, many High Efficiency Video Coding (HEVC) video steganography algorithms based on Intra Prediction Mode (IPM) have been proposed. However, the existing IPM-based video steganalysis algorithms are almost designed for H.264/AVC videos, without considering the unique coding techniques in HEVC, which is the latest video codec standard. Thus, it is of significant value to study IPM-based steganalysis for HEVC videos. In this paper, the general process of IPM-based HEVC steganography is modelled for the first time, and we find that the basic distortion existing in the change of the relationships between each embedded IPM and the adjacent IPMs. By exploiting these weaknesses, we propose a novel IPM steganalysis algorithm based on the Relationship of Adjacent IPMs (RoAIPM) feature. In detail, the RoAIPM is extracted by generating different directional Gray-Level Co-occurrence Matrixes (GLCMs) and texture characteristics of three refilled matrixes: MPM-IPM matrix, Left-IPM matrix and Up-IPM matrix. Experimental results show that, the proposed RoAIPM feature is very sensitive to the little change introduced by IPM-based steganography. Regardless of whether the feature is after dimension reduction or not, in various coding conditions, the proposed steganalysis can both present a well higher detection accuracy against the latest IPM-based HEVC steganography methods and achieve the lowest computational complexity compared with the state-of-the-art works.
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