Abstract: With the rapid development of telemedicine, the secure management and transmission of patient privacy data face significant challenges. To achieve unified management and secure storage of electronic medical records (EMRs) and medical images, this paper proposes an encoding-domain hidden encryption scheme for multimodal medical data. Specifically, a string-to-image transformation algorithm based on UTF-8 encoding and positional numeral decomposition is designed to convert EMRs into encoded images, ensuring data privacy and security. To facilitate integrated management of multimodal data, an improved HiNet reversible network is introduced to embed medical images into encoded images. By incorporating the Kullback-Leibler (KL) divergence to constrain the distribution distance, the scheme enhances the accuracy and robustness of image embedding and reconstruction. Furthermore, to strengthen the security of the encoded images, a bit-level encryption algorithm based on the logic-sine-cosine chaotic system is designed, leveraging its high sensitivity and nonlinear characteristics for robust encryption. Experimental results demonstrate that the proposed encoding-domain hidden encryption scheme effectively ensures data security while enabling lossless access to EMRs and high-quality recovery of medical images, offering enhanced confidentiality for secure management of multimodal data in telemedicine.

Key words: Bit-level chaotic encryption, UTF-8 encoding, reversible network steganography, multimodal data, privacy protection