Title :
Steganalysis of Youtube Compressed Video Using High-order Statistics in 3D DCT Domain
Author :
Zhao, Hong ; Wang, Hongxia ; Malik, Hafiz
Author_Institution :
Sch. of Inf. Sci. & Technol., Southwest Jiaotong Univ., Chengdu, China
Abstract :
This papers presents a novel steganalysis scheme for YouTube compressed video. The proposed scheme exploits spatial-temporal correlation between adjacent frames. To this end, 3D Discrete Cosine Transform (DCT) is used to capture this correlation. Statistical features sensitive to data hiding such as absolute central moments, skewness, kurtosis, and Markov features are used as classifying statistics. Unsupervised K-means clustering is used to distinguish between the cover- and the stego-videos. Effectiveness of the proposed scheme is tested using 40 standard videos. Experimental results reveal that the proposed scheme is capable of detecting the presence of hidden message in the stego-YouTube videos.
Keywords :
Markov processes; discrete cosine transforms; image classification; pattern clustering; social networking (online); spatiotemporal phenomena; statistical analysis; steganography; video coding; 3D DCT domain; 3D discrete cosine transform domain; Markov features; YouTube compressed video steganalysis; absolute central moments; cover-videos; data hiding; hidden message detection; high-order statistics classification; kurtosis; skewness; spatial-temporal correlation; stego-videos; unsupervised k-means clustering; video frames; Correlation; Discrete cosine transforms; Feature extraction; Image coding; Markov processes; Video compression; YouTube; 3D-DCT; Video Steganalysis;
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2012 Eighth International Conference on
Conference_Location :
Piraeus
Print_ISBN :
978-1-4673-1741-2
DOI :
10.1109/IIH-MSP.2012.52
