Abstract
Steganalysis targets to detect the existence of hidden information in a given content. In this paper we propose to use a local feature set which is designed to enhance discrimination of features obtained from a cover and a stego mesh. The proposed feature captures the fine deformation of the 3D mesh surface induced by a steganography or watermarking method. In our 3D steganalysis approach, in addition, we apply the homogeneous kernel map to the local feature set, which make it possible to bring much more discrimination via non-linear mapping. The proposed feature set and its combination with the homogeneous feature map have shown good performance on two different steganography and watermarking algorithm with a well known and widely used 3D mesh database through repeated experiments.
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References
Bateman, P., Schaathun, H.G.: Image steganography and steganalysis. Master’s thesis, University of Surrey, United Kingdom
Ohbuchi, R., Takahashi, S., Miyazawa, T., Mukaiyama, A.: Watermarking 3D polygonal meshes in the mesh spectral domain. In: Graphics Interface (GI), vol. 2001, pp. 9–17. Citeseer (2001)
Cho, J.W., Prost, R., Jung, H.Y.: An oblivious watermarking for 3-D polygonal meshes using distribution of vertex norms. IEEE Trans. Sig. Process. (TSP) 55(1), 142–155 (2007)
Chao, M.W., Lin, C.H., Yu, C.W., Lee, T.Y.: A high capacity 3D steganography algorithm. IEEE Trans. Vis. Comput. Graph. (TVCG) 15(2), 274–284 (2009)
Yang, Y., Ivrissimtzis, I.: Mesh discriminative features for 3D steganalysis. ACM Trans. Multimedia Comput. Commun. Appl. (TOMM) 10(3), 27 (2014)
Yang, Y., Pintus, R., Rushmeier, H., Ivrissimtzis, I.: A steganalytic algorithm for 3D polygonal meshes. In: IEEE International Conference on Image Processing (ICIP), pp. 4782–4786. IEEE (2014)
Yang, Y., Pintus, R., Rushmeier, H., Ivrissimtzis, I.: A 3D steganalytic algorithm and steganalysis-resistant watermarking. IEEE Trans. Vis. Comput. Graph. (TVCG) (in press). doi:10.1109/TVCG.2016.2525771
Li, Z., Bors, A.G.: 3D mesh steganalysis using local shape features. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2144–2148. IEEE (2016)
Boroumand, M., Fridrich, J.: Boosting steganalysis with explicit feature maps. In: ACM Workshop on Information Hiding and Multimedia Security (IH & MMSec), pp. 149–157. ACM (2016)
Perronnin, F., Sénchez, J., Xerox, Y.L.: Large-scale image categorization with explicit data embedding. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2297–2304. IEEE (2010)
Vedaldi, A., Zisserman, A.: Efficient additive kernels via explicit feature maps. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 34(3), 480–492 (2012)
Peyre, G., Cohen, L.: Surface segmentation using geodesic centroidal tesselation. In: International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT), pp. 995–1002. IEEE (2004)
Lyu, S., Farid, H.: Detecting hidden messages using higher-order statistics and support vector machines. In: Petitcolas, F.A.P. (ed.) IH 2002. LNCS, vol. 2578, pp. 340–354. Springer, Heidelberg (2003). doi:10.1007/3-540-36415-3_22
Kodovsky, J., Fridrich, J., Holub, V.: Ensemble classifiers for steganalysis of digital media. IEEE Trans. Inf. Forensics Secur. (TIFS) 7(2), 432–444 (2012)
Cogranne, R., Fridrich, J.: Modeling and extending the ensemble classifier for steganalysis of digital images using hypothesis testing theory. IEEE Trans. Inf. Forensics Secur. (TIFS) 10(12), 2627–2642 (2015)
Wang, K., Torkhani, F., Montanvert, A.: A fast roughness-based approach to the assessment of 3D mesh visual quality. Comput. Graph. 36(7), 808–818 (2012)
Fawcett, T.: An introduction to ROC analysis. Pattern Recogn. Lett. 27(8), 861–874 (2006)
Acknowledgments
This work was supported by Samsung Research Funding Center of Samsung Electronics under Project Number SRFC-IT1402-05.
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Kim, D., Jang, HU., Choi, HY., Son, J., Yu, IJ., Lee, HK. (2017). Improved 3D Mesh Steganalysis Using Homogeneous Kernel Map. In: Kim, K., Joukov, N. (eds) Information Science and Applications 2017. ICISA 2017. Lecture Notes in Electrical Engineering, vol 424. Springer, Singapore. https://doi.org/10.1007/978-981-10-4154-9_42
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DOI: https://doi.org/10.1007/978-981-10-4154-9_42
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