Hybrid wet paper coding mechanism for steganography employing n-indicator and fuzzy edge detector

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Abstract

Data hiding technique can facilitate security and the safe transmission of important information in the digital domain, which generally requires a high embedding payload and good stego image quality. Recently, a steganographic framework known as wet paper coding has been utilized as an effective strategy in image hiding to achieve the requirements of high embedding payload, good quality and robust security. In this paper, besides employing this mechanism as a fundamental stage, we take advantage of two novel techniques, namely, an efficient n-indicator and a fuzzy edge detector. The first is to increase the robustness of the proposed system to guard against being detected or traced by the statistics methods while allowing the receiver without knowledge of secret data positions to retrieve the embedded information. The second is to improve the payload and enhance the quality of stego image. The experimental results show that our proposed scheme outperforms its ability to reduce the conflict among three steganography requirements.

Section snippets

Chin-Chen Chang received his B.S. degree in applied mathematics in 1977 and his M.S. degree in computer and decision sciences in 1979, both from the National Tsing Hua University, Hsinchu, Taiwan. He received his Ph.D. in computer engineering in 1982 from the National Chiao Tung University, Hsinchu, Taiwan. During the academic years of 1980–1983, he was on the faculty of the Department of Computer Engineering at the National Chiao Tung University. From 1983 to 1989, he was on the faculty of the

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    Chaumont et al. (2013) presented a method to protect the color information of images by providing free access to the corresponding gray-level images, and it is based on a color reordering algorithm after a quantization step. Chang et al. (2010) applied two novel techniques for an edge detector, where the first is to increase the robustness to guard against detectors while the second is to improve the payload and enhance the quality of the stego image. Luo et al. (2010) implemented LSB matching, revisiting image steganography and an edge adaptive scheme that can select the embedding regions according to the size of the secret message and the difference between two consecutive pixels in the cover image.

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Chin-Chen Chang received his B.S. degree in applied mathematics in 1977 and his M.S. degree in computer and decision sciences in 1979, both from the National Tsing Hua University, Hsinchu, Taiwan. He received his Ph.D. in computer engineering in 1982 from the National Chiao Tung University, Hsinchu, Taiwan. During the academic years of 1980–1983, he was on the faculty of the Department of Computer Engineering at the National Chiao Tung University. From 1983 to 1989, he was on the faculty of the Institute of Applied Mathematics, National Chung Hsing University, Taichung, Taiwan. From 1989 to 2004, he worked as a professor in the Institute of Computer Science and Information Engineering at National Chung Cheng University, Chiayi, Taiwan. Since 2005, he has worked as a professor in the Department of Information Engineering and Computer Science at Feng Chia University, Taichung, Taiwan. Dr. Chang is a Fellow of IEEE, a Fellow of IEE and a member of the Chinese Language Computer Society, the Chinese Institute of Engineers of the Republic of China, and the Phi Tau Phi Society of the Republic of China. His research interests include computer cryptography, data engineering, and image compression.

Jung-San Lee received the B.S. degree in computer science and information engineering in 2002 and his Ph.D. in computer science and information engineering in 2008, both from the National Chung Cheng University, Chiayi, Taiwan. Since 2008, he has worked as an assistant professor in the Department of Information Engineering and Computer Science at Feng Chia University, Taichung, Taiwan. His current research interests include electronic commerce, information security, cryptography, and mobile communications.

T. Hoang-Ngan Le received her B.S. degree in Information Technology from the University of Science, Vietnam National University–HCMC, in 2005 and her M.S. degree from the same university in 2009. She is currently a Lecturer of the Department of Computer Science, Faculty of Information Technology, University of Science, Vietnam National University–HCMC, Vietnam. Her research interests include image processing, audio processing, and multimedia security.

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