H.265/HEVC Video Steganalysis Based on CU Block Structure Gradients and IPM Mapping

TL;DR

This paper introduces a novel H.265/HEVC video steganalysis method that detects covert embedding based on CU block structure perturbations using a gradient map and a Transformer-based neural network.

Contribution

It pioneers a CU block structure-based steganalysis approach with a new gradient map and a specialized neural network architecture, improving detection accuracy.

Findings

Consistently outperforms existing methods across various steganography techniques.

Effective under different quantization parameters and resolution settings.

Provides a new paradigm for CU block structure steganalysis in H.265/HEVC videos.

Abstract

Existing H.265/HEVC video steganalysis research mainly focuses on detecting the steganography based on motion vectors, intra prediction modes, and transform coefficients. However, there is currently no effective steganalysis method capable of detecting steganography based on Coding Unit (CU) block structure. To address this issue, we propose, for the first time, a H.265/HEVC video steganalysis algorithm based on CU block structure gradients and intra prediction mode mapping. The proposed method first constructs a new gradient map to explicitly describe changes in CU block structure, and combines it with a block level mapping representation of IPM. It can jointly model the structural perturbations introduced by steganography based on CU block structure. Then, we design a novel steganalysis network called GradIPMFormer, whose core innovation is an integrated architecture that combines convolutional local embedding with Transformer-based token modeling to jointly capture local CU boundary perturbations and long-range cross-CU structural dependencies, thereby effectively enhancing the capability to perceive CU block structure embedding. Experimental results show that under different quantization parameters and resolution settings, the proposed method consistently achieves superior detection performance across multiple steganography methods based on CU block structure. This study provides a new CU block structure steganalysis paradigm for H.265/HEVC and has significant research value for covert communication security detection.