| Summary: | 碩士 === 國立臺北科技大學 === 自動化科技研究所 === 106 === Cloud computing is an Internet-based computing model that shares computing resources such as computers, servers, and storage. However, if the size of cloud data is large (e.g., medical images), their transition through the Internet is time consuming. Cloud data authentication is another problem that should be addressed.
To address the aforementioned problems, this study presents a novel data hiding method based on the block truncation coding (BTC) image compression technique. This method has two advantages: reduces image size and increases security. This study also proposes a block classification scheme for determining smooth blocks, complex 1 blocks, and complex 2 blocks in an image. Secret data are embedded in these three block types using different approaches. To improve the quality of images without damaging the secret data, we propose a progressive data hiding strategy and integrating an iteration-based halftoning method into BTC. According to experimental results, the proposed method outperforms existing methods in both embedding capacity and image quality evaluations.
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