Aiming at the problem that the existing 3D model information hiding algorithms cannot effectively resist uneven compression, a multi-carrier low-density information hiding algorithm based on multiple fusion states was proposed. Firstly, multiple 3D models were positioned, oriented and stereotyped by translation and scaling. Secondly, the 3D models were rotated at different angles and merged by using the center point as merging point to obtain multiple fusion states. Thirdly, local height and Mean Shift clustering analysis were used to divide the energy of the vertices of the fusion state model, obtaining the vertices with different energies. Finally, by changing the vertex coordinates, the secret information changed by Arnold scrambling was quickly hidden in multiple fusion states and 3D models. Experimental results show that the proposed algorithm is robust against uneven compression attacks and has high invisibility.

Aiming at the problem that some 3D model-based information hiding algorithms are incompetent against combined attacks, a new strategy based on feature point labeling and clustering was proposed. Firstly, edge folding was adopted to achieve mesh simplification and all the vertexes were labeled in order by their energy level. Secondly, the ordered vertexes were clustered and re-ordered by using local height theory and Mean Shift clustering analysis. Lastly, hidden information and cover model carrier information were optimized, matched and modified by Logistic chaos mapping scrambling and genetic algorithm, completing the final hiding. The data in hiding areas were labeled and screened locally and globally according to the energy weight, which is good for the robustness and transparency of the algorithm. The experimental results show that, compared with 3D information hiding algorithms based on inscribed sphere and outer skeleton, the robustness of the proposed algorithm against single or joint attacks is significantly improved, and it also has the same degree of invisibility.

To solve the problem of low invisibility and weak anti-attacking ability in the traditional information hiding algorithm, an information hiding algorithm based on compression sensing was proposed. Firstly, the carrier image was operated by first-order GHM (Geronimo Hardin Massopust) multiwavelet transform, and the obtained region in medium energy level was processed by first-order GHM transform again to get HH component, which was decomposed by the Singular Value Decomposition (SVD). Secondly, the secret image was disposed by the wavelet transform, and the obtained wavelet coefficient was processed by compressed sensing in order to get the measurement matrix. Then the elements of the matrix were decomposed by SVD. Finally, the singular value of the carrier image was replaced by the singular value of the secret image to finish the secret information embedding. The experiment shows that compared with existing two information hiding algorithms, the invisibility has been improved by 5.99% and 22.11% respectively; and the robustness against some common attacks such as low-pass filtering, salt and pepper noise, Gaussian noise and JPEG compression has been improved by 4.11% and 11.53% averagely.

Aiming at the problem of weak robustness to geometric attack in 3D model information hiding algorithms, an information hiding algorithm based on 3D model spherical segmentation was proposed. Firstly, the 3D model was preprocessed by principal component analysis, spherical coordinate transformation, spherical segmentation and partition sorting. Then, the points with larger normal vector in stereo partition are taken as feature points. The feature points were carried out wavelet transform according to the amount of secret information to be embedded. Finally, the secret information after scrambled operation was embedded into the pre-processed carrier to generate the secret 3D model. The experimental results show that the algorithm is invisible and has good robustness to random noise, heavy mesh and other common attacks.

In order to solve the problems of security and capacity of confidential information during public network transmission, an information hiding algorithm based on the High Efficiency Video Coding (HEVC) background was proposed. The background image of multi-view images in HEVC was used as the carrier. Firstly, the background image was decomposed into three gray-scale components by using lαβ color space theory. Then, the image components such as α and β were transformed by Discrete Cosine Transform (DCT) method. Finally, the confidential information was embedded into the region of carrier repeatedly. With relative low energy weight, the mid-frequency coefficient regions of α and β components after DCT were both chosen as the hidden regions to be embedded repeatedly with the confidential information, which makes the proposed algorithm have good invisibility and robustness. The experimental results show that, compared with the algorithms based on intra-frame and inter-frame, the invisibility of the proposed algorithm was improved respectively by about 16.1% and 11.4% while the robustness of the proposed algorithm was increased respectively by about 55.5% and 20.2%.

Aiming at the confidential communication based on information hiding technology, an information hiding algorithm using interval analysis of values on Z-axis for the vertical profile of three-dimensional (3D) models was proposed. First, the 3D model was scaled and rotated disproportionately according to fixed size and angle respectively, and the vertical profile could be obtained by horizontal mapping. Second, the vertical profile was mapped into the two-dimensional coordinate system and the values on the vertical axis could be determined using a fixed step size. Last, the vertical values were converted into binary numbers with interval constraints according to the fixed threshold. By disproportionate scaling with fixed size, the algorithm could be effective against the scaling attack. According to the fixed rotated angle and step size, the data could be embedded in redundancy of the whole model and the algorithm could be robust against cutting. The experimental results illustrate that this algorithm is of strong robustness against the random noise under 0.2%, re-meshing and non-uniform simplification.

In view of the contradiction between capability, invisibility and robustness of the existing information hiding algorithms, a preprocessing algorithm for digital image based on CL (Chui-Lian) multi-wavelet transform and Combination Bit Plane (CBP) was proposed. Then the digital image preprocessed by CL multi-wavelet and CBP was taken as the cover image to embed secret information for confidential communication and image sharing. CL multi-wavelet transform could divide the cover image into four lowest resolution sub-images with different energy level. And CBP method could analyze the above four sub-images into different bit planes as the final embedding regions. During the hiding procedure, robust information, secret information and fragile information could be embedded according to the energy and robustness characteristics of the embedding regions. The experimental results show that the robustness against several common attacks described in this paper has certain enhancement compared with other two methods when the embedding rate is 25%. The Peak Signal-to-Noise Ratio (PSNR) is increased by 37.16% and 20.00% respectively compared with Discrete Cosine Transform-Least Significant Bit (DCT-LSB) and Discrete Wavelet Transform -Least Significant Bit (DWT-LSB) algorithm.