Protecting Secret Data using RDE and Fuzzy Logic to Specify the Embedding Level Along with the rapid increase in information technology, there is a challenge in data security. For this reason, data protection has been a focus for some decades. One of the methods, called data hiding, is introduced to solve this security issue. It can protect secret data; nevertheless, the quality of the resulted stego data for a certain amount of the secret is limited. Moreover, the reversibility of the algorithm is also a concern. In this research, we intend to improve the method by combining Reduced Difference Expansion (RDE) and the concept of fuzzy logic, by considering some factors, such as brightness and its entropy value. It is to specify the number of embedding, which should be done for each block in an image. Therefore, the embedding level is dynamic, which means that it may be different for each block. The experimental result shows that this proposed method works well; adaptive such that it follows the characteristics of the carrier. Moreover, the method is also reversible that both the secret data and the carrier can be successfully reconstructed.

Reversible Data Hiding Based Key Region Protection Method in Medical Images The transmission of medical image data in an open network environment is subject to privacy issues including patient privacy and data leakage. In the past, image encryption and informationhiding technology have been used to solve such security problems. But these methodologies, in general, suffered from difficulties in retrieving original images. We present in this paper an algorithm to protect key regions in medical images. First, coefficient of variation is used to locate the key regions, a.k.a. the lesion areas, of an image; other areas are then processed in blocks and analyzed for texture complexity. Next, our reversible datahiding algorithm is used to embed the contents from the lesion areas into a hightexture area, and the Arnold transformation is performed to protect the original lesion information. In addition to this, we use the ciphertext of the basic information about the image and the decryption parameter to generate the Quick Response (QR) Code to replace the original key regions. Consequently, only authorized customers can obtain the encryption key to extract information from encrypted images. Experimental results show that our algorithm can not only restore the original image without information loss, but also safely transfer the medical image copyright and patientsensitive information.