Reversible Data Hiding in Encrypted Images based on MSB Prediction and Huffman Coding Sourse: arXiv preprint, arXiv:1812.09499, 2018 (Submit to IEEE Trans. Multimedia) Authors: Youzhi Xiang, Zhaoxia Yin and Xinpeng Zhang Speaker: Wang Xu Date: 2019/05/23

Outline Introduction Related work Proposed method Experiment results Conclusions

Embedded, encrypted image Introduction (1/2) Encrypted secret data Secret data Original image Encrypted image Embedded, encrypted image

Embedded, encrypted image Introduction (2/2) Original image Secret data Embedded, encrypted image Secret data Original image

Related work – MED predictor 𝑞 𝑖,𝑁𝑊 𝑞 𝑖,𝑁 𝑞 𝑖,𝑊 𝑝 𝑖 192 191 176 99 103 101 75 182 70 177

Proposed method – Label map generation 136 150 147 156 136 150 147 𝑞 𝑖 𝑝 𝑖 Different bit 𝑝 𝑖 : 150 1 1 Label = 4 𝑞 𝑖 : 156 1 1 Same bits Ignore bits

Proposed method – Image encryption Bit level encryption Calculate the encrypted pixel

Proposed method – Label map coding and embedding (1/4) Static Huffman codings

Proposed method – Label map coding and embedding (2/4) 1110 𝑝 𝑖 : 176 1 1 𝑞 𝑖 : 150 1 1 Auxiliary information Encrypted 𝑞 𝑖 1 1 Label embedded 𝑞 𝑖 1 1

Proposed method – Label map coding and embedding (3/4) 100 𝑝 𝑖 : 148 1 1 𝑞 𝑖 : 150 1 1 Encrypted 𝑞 𝑖 1 Label embedded 𝑞 𝑖 1 1 1 Additional data embedding

Proposed method – Label map coding and embedding (4/4) First row the length of the auxiliary information: 20 bits + Reference pixels Prediction area label map: 32bits First column

Proposed method – Data hiding First row Reference pixels Secret data Auxiliary information First column

Proposed method – Data Extraction and Image Recovery Label map information Image recover First row Auxiliary information Unpredictable area Secret data Auxiliary information First column Data extract Secret data

Experiment results (1/7)

Experiment results (2/7)

Experiment results (3/7)

Experiment results (4/7) [23] P. Bas, T. Filler, and T. Pevný, “Break our steganographic system—The ins and outs of organizing BOSS,” in Proc. 13th Int. Conf., pp. 59–70, May, 2011. Available: http://dde.binghamton.edu/download/ [24] P. Bas and T. Furon. Image Database of BOWS-2. Accessed: Jun. 20, 2017. [Online]. Available: http://bows2.ec-lille.fr/ [25] G. Schaefer and M. Stich, “UCID: An uncompressed color image database,” Proc. SPIE Electronic Imaging, Storage and Retrieval Methods and Applications for Multimedia, vol. 5307, pp. 472–480, 2003. Available: http://vision.doc.ntu.ac.uk/

Experiment results (5/7) [20] P. Puteaux and W. Puech, “An Efficient MSB Prediction-Based Method for High-Capacity Reversible Data Hiding in Encrypted Images[J],” IEEE Trans. Inf. Forensics Security, vol. 13, no. 7, pp. 1067–1681, Jan, 2018. [21] Y. Puyang, Z. Yin, and Z. Qian, “Reversible Data Hiding in Encrypted Images with Two-MSB Prediction,” IEEE International Workshop on Information Forensics and Security (WIFS), 2018. [22] S .Yi and Y. Zhou, “Separable and Reversible Data Hiding in Encrypted Images using Parametric Binary Tree Labeling[J],” IEEE Transactions on Multimedia, PP(99):1-1, 2018.

Experiment results (6/7)

Experiment results (7/7)

Conclusions The proposed method has greatly improved the embedding capacity compared to the most advanced algorithms.

Thanks