A HEVC Steganalysis Algorithm Based on Relationship of Adjacent Intra Prediction Modes

Henan Shi, Tanfeng Sun, Zhaohong Li
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引用次数: 1

Abstract

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.
基于相邻内预测模式关系的HEVC隐写分析算法
目前,已经提出了许多基于帧内预测模式(IPM)的高效视频编码(HEVC)视频隐写算法。然而,现有的基于ipm的视频隐写分析算法几乎都是针对H.264/AVC视频设计的,没有考虑到HEVC中独特的编码技术,HEVC是最新的视频编解码标准。因此,研究基于ipm的HEVC视频隐写分析具有重要的应用价值。本文首次对基于IPM的HEVC隐写的一般过程进行了建模,发现每个嵌入IPM与相邻IPM之间关系的变化存在着基本的失真。利用这些缺陷,我们提出了一种新的基于相邻IPM关系特征的IPM隐写算法。通过生成不同方向的灰度共生矩阵(glcm)和三种填充矩阵的纹理特征来提取RoAIPM: MPM-IPM矩阵、Left-IPM矩阵和Up-IPM矩阵。实验结果表明,所提出的RoAIPM特征对基于ipm的隐写所带来的微小变化非常敏感。无论特征是否经过降维处理,在各种编码条件下,相对于基于ipm的HEVC隐写方法,本文所提出的隐写方法都具有较高的检测精度,并且与目前最先进的隐写方法相比,计算复杂度最低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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