4.6 Article

A novel medical image encryption based on cellular automata with ROI position embedded

Journal

MULTIMEDIA TOOLS AND APPLICATIONS
Volume 81, Issue 5, Pages 7323-7343

Publisher

SPRINGER
DOI: 10.1007/s11042-021-11799-8

Keywords

Region of interest; Medical image security; Life-like cellular automata; Histogram shifting

Funding

  1. National Natural Science Foundation of China [61902110]
  2. Fundamental Research Funds for the Central Universities [B200202178]
  3. National Key Technology Research and Development Program of theMinistry of Science and Technology of China [2018YFC0407105]
  4. Key Technology Project of China Hueneng Group [SGTYHT/19-JS-217, HHNKJ19 H12]

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Medical image encryption is important for protecting privacy and preventing malicious attacks. Research on encryption schemes based on regions of interest (ROI) can improve efficiency and security, and the use of life-like cellular automata and histogram shifting is a novel encryption method.
Medical images are critical to medical diagnosis and clinical treatment. However, the transmission of medical images over the Internet without any protection may cause malicious attacks and privacy leakage. Different from the natural image, the medical image contains a large number of black backgrounds. For privacy protection, the background of the medical image is unnecessary to be encrypted. Therefore, the encryption scheme based on the region of interest (ROI) is especially fit for medical image encryption, which paves a promising way to improve efficiency without sacrificing security. However, most of the existing ROI-based encryption schemes occupy exceptional space and time to transmit the marking information of ROI. To overcome this drawback, we present a novel ROI encryption scheme based on life-like cellular automata (life-like CA) and histogram shifting (HS). In the encryption stage, the life-like CA with balanced rules is used to encrypt ROI. Unlike most known image encryption algorithms, this model can support parallel computing. Furthermore, the marking information of ROI and electronic medical record (EMR) are embedded into the cipher image, which reduce the number of bits to be transmitted. The experiments and security analysis demonstrate that the proposed scheme can effectively protect ROI of different types and sizes of medical images, and is robust in resisting various attacks.

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