Dissertation > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device

Research on Video Steganography and Video Steganalysis

Author XuChangYong
Tutor PingXiJian
School PLA Information Engineering University
Course Military Intelligence
Keywords Information hiding Steganography Steganalysis Digital video Motion vector Error-correction code Hidden information detection Active attack Temporal correlation Spatial correlation
CLC TP391.41
Type PhD thesis
Year 2009
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Information hiding is one of important research subjects in the field of information security. As a main branch of information hiding, steganography has received significant attention from both industry and academia. Steganography is the art of concealing the very existence of communications by embedding the secret information into the open digital media, such as digital image, digital video, and so on. The technique opposed to steganography is called steganalysis, the purpose of which is to expose the presence of secret information. Digital video is one kind of familiar digital media on the Internet. With the development of video compression technique and stream media operation, the application area of video is more and more widely, for example, video on demand and video conference. Moreover, the gradual prevalence of portable video camera and the video edit software, people can easily record, edit and release video on the Internet, which makes the video transmission more frequently. In addition, the characteristics of large data amount, abundant content and complicated statistics for video make it must be an important carrier for steganography. Consequently, it is of great importance to study the technique of video steganography and the opposed technique - video steganalysis.Keeping up with the newly developed techniques of steganography and staganalysis, and according to the analysis to video data, this thesis focus on the techniques of video steganography and video steganalysis. The main contributions of this thesis are summarized as follows:1. A steganographic method in compressed video stream based on motion vector. According to the fact that there are abundant motion vectors in video stream, a steganographic method based on motion vector is proposed. On a GOP by GOP basis, the strategy of redundant embedding and control information embedding is utilized to resist frame synchronization attacks. The secret information is embedded into the motion vectors of inter-encoded frames by redundant embedding firstly, then the control information generated during redundant embedding is embedded into the DCT coefficient of intra-encoded frames. Experimental results show the method can keep the quality of stego video, and resist the temporal synchronization attacks as frame inserting and frame dropping.2. A steganographic method in compressed video stream based on error-correction code. According to the thorough analysis to MPEG compressed video data, a steganographic method for embedding secret information in DCT coefficients which are not differential encoded is proposed. Utilizing the principle of steganography based on error-correction code, a strategy of two-time embedding is designed to embed secret information. That’s to say, the secret information is firstly embedded into the error-correction codeword, then by modifying the level value of run-level pair corresponding to the DCT coefficient which is not differential encoded, the stego codeword obtained by first time embedding is secondly embedded. Moreover, measures are taken for the purpose of preserving the video stream size. Experimental results show the method has a good visual and statistical imperceptibility, and can keep the nearly invariant size of video stream. 3. A hidden information detection method and an active attack method for MSU StegoVideo. MSU StegoVideo is an open video steganography software on the Internet, the embedding algorithm of which has a strong robustness. By the experiment of data embedding and extraction, the embedding mechanism is revealed and the distribution characteristic of the embedded data is analyzed. According to the analysis, on the condition of stego-only attack, a hidden information detection method utilizing the asymmetric distribution of block artifacts and the difference of edge discontinuity, and an active method based on inter-frame collusion is proposed. Experimental results show the detection method can accurately find the existence of hidden information, and the active attack can effectively destroy the hidden information on the premise that the video quality is preserved. The two methods can be combined to detect and destroy the covert communication which is executed by MSU StegoVideo.4. A video steganalysis method based on spatial-temporal correlation. Temporal correlation and spatial correlation are basic characteristics of video sequence. Aimed at spread-spectrum embedding for video which can resist many attacks such as video compression and noise addition, the data embedding is modeled as the addition of additive Gaussian noise. By analyzing the influence to temporal correlation and spatial correlation of video owing to noise addition, a steganalysis method based on spatial-temporal correlation is proposed. The method uses difference image histogram of four directions to measure the influence of spatial correlation, and temporal correlation is measured by the histogram of frame difference. According to the difference of the histograms after data embedding, the statistical parameters derived from the histograms are used as feature vectors to differentiate the change of spatial and temporal correlation. In the end, the stego video can be discriminated from the cover video by using SVM classifier to train and classify the feature vectors. Experimental results show it is effective to detect the existence of hidden information for both uncompressed video and compressed video. At the same time, it is testified that by the combination of spatial correlation and temporal correlation, the detection performance is improved.

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