An edge-based steganography algorithm for hiding text into images
Alomirah, Reem Abdulrahman
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Citation:Alomirah, R. A. (2019). An edge-based steganography algorithm for hiding text into images. An unpublished thesis submitted in partial fulfilment of the requirements for the degree of Master of Computing, Unitec Institute of Technology, Auckland, New Zealand.
Permanent link to Research Bank record:https://hdl.handle.net/10652/4502
RESEARCH QUESTIONS: • How can I improve existing steganography methods in terms of capacity and transparency? • How can I reduce the complexity of existing steganography methods? • How can I increase the robustness of existing steganography methods? One of the biggest concerns in data communication is data security. There are several approaches to securely sending data over the network, one of which is steganography. Steganography refers to techniques that hide information inside other media in such a way that no one will notice. The cover media that can accommodate secret information include text, audio, image, and video. Images are the most popular covering media in steganography, because they are heavily used in daily applications and have high redundancy in representation. Steganography techniques are classified into three major groups: transform domain techniques, spatial domain techniques, and adaptive techniques. In this thesis, I propose an adaptive algorithm for hiding information in RGB images. To minimise visual perceptible distortion, the proposed algorithm uses edge pixels for embedding data. It detects the edge pixels in the image using the Sobel filter. Then, the message is embedded into the LSBs of the blue channel of the edge pixels. To resist statistical attacks, the distribution of the blue channel of the edge pixels is used when embedding data in the cover image. The research method used in this thesis is experimental research. The proposed algorithm has been implemented in MATLAB and has been evaluated in terms of various factors: capacity, signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), Chisquare index, and execution time using eight RGB pictures from USC-SIPI Image Database. The results showed that the algorithm offers high capacity for hiding data in cover images (9-111 KB data can be hidden depending on the picture when using 4 LSBs); it does not distort the quality of the stego image (SNR ≥ 32 and PSNR ≥ 41); it is robust enough against statistical attacks (Chi-Square index is below 0.5); and its execution time is short enough for online data transfer (below one second for all experimentations). Also, the results showed that the proposed algorithm outperforms similar approaches for all evaluation metrics.