A Steganalytic Algorithm to Detect DCT-based Data Hiding Methods for H.264/AVC Videos

Abstract

This paper presents an effective steganalytic algorithm to detect Discrete Cosine Transform (DCT) based data hiding methods for H.264/AVC videos. These methods hide covert information into compressed video streams by manipulating quantized DCT coefficients, and usually achieve high payload and low computational complexity, which is suitable for applications with hard real-time requirements. In contrast to considerable literature grown up in JPEG domain steganalysis, so far there is few work found against DCT-based methods for compressed videos. In this paper, the embedding impacts on both spatial and temporal correlations are carefully analyzed, based on which two feature sets are designed for steganalysis. The first feature set is engineered as the histograms of noise residuals from the decompressed frames using 16 DCT kernels, in which a quantity measuring residual distortion is accumulated. The second feature set is designed as the residual histograms from the similar blocks linked by motion vectors between inter-frames. The experimental results have demonstrated that our method can effectively distinguish stego videos undergone DCT manipulations from clean ones, especially for those of high qualities.