With the rapid advancement of technology, the Internet of Medical Things (IoMT) has become an invaluable tool in healthcare. A vast amount of medical image transmission takes place through IoMT, enabling remote diagnostics and patient monitoring. However, the sensitive nature of patient data makes it vulnerable to unauthorized access, modification, or exposure during transmission. To address these challenges ensure the security, confidentiality, and authenticity of medical images, a blind region-based data hiding scheme known as Medical Image Watermarking (MIW) is proposed. This technique improves the protection of medical images while they are transmitted over IoMT, protecting patient information against potential threats. Medical images are divided into two parts: the Region of Interest (RoI) and the Region of Non-Interest (RoNI). The proposed Medical Image Watermarking (MIW) technique aims to protect the RoI during transmission while ensuring the confidentiality of Electronic Health Records (EHR). The RoI is crucial for medical diagnosis, while the RoNI, which does not impact diagnosis, is utilized to embed EHR and authentication information. The binary EHR, is embedded into the RoNI using a hybrid Discrete Wavelet Transform-Singular Value Decomposition (DWT-SVD) approach, ensuring high imperceptibility and robustness. For authenticity, the hospital logo is merged with the patient’s record to form a single EHR, which is then transmitted as a single image. To guarantee confidentiality, the EHR is encrypted using a randomly generated secret key based on the Double Conditional Linear Congruential Generator (DCLCG) approach before embedding. Experimental results demonstrate that the proposed scheme is highly robust against various image processing attacks. Furthermore, the proposed method outperforms the state-of-the-art schemes in watermarking characteristics, making it a superior solution to secure medical images in IoMT environments.

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Secure Transmission of Medical Images in IoMT for Smart Cities Using Data Hiding Scheme

  • Kilari Jyothsna Devi,
  • Ravuri Daniel,
  • Bode Prasad,
  • B. Ratna Sunil

摘要

With the rapid advancement of technology, the Internet of Medical Things (IoMT) has become an invaluable tool in healthcare. A vast amount of medical image transmission takes place through IoMT, enabling remote diagnostics and patient monitoring. However, the sensitive nature of patient data makes it vulnerable to unauthorized access, modification, or exposure during transmission. To address these challenges ensure the security, confidentiality, and authenticity of medical images, a blind region-based data hiding scheme known as Medical Image Watermarking (MIW) is proposed. This technique improves the protection of medical images while they are transmitted over IoMT, protecting patient information against potential threats. Medical images are divided into two parts: the Region of Interest (RoI) and the Region of Non-Interest (RoNI). The proposed Medical Image Watermarking (MIW) technique aims to protect the RoI during transmission while ensuring the confidentiality of Electronic Health Records (EHR). The RoI is crucial for medical diagnosis, while the RoNI, which does not impact diagnosis, is utilized to embed EHR and authentication information. The binary EHR, is embedded into the RoNI using a hybrid Discrete Wavelet Transform-Singular Value Decomposition (DWT-SVD) approach, ensuring high imperceptibility and robustness. For authenticity, the hospital logo is merged with the patient’s record to form a single EHR, which is then transmitted as a single image. To guarantee confidentiality, the EHR is encrypted using a randomly generated secret key based on the Double Conditional Linear Congruential Generator (DCLCG) approach before embedding. Experimental results demonstrate that the proposed scheme is highly robust against various image processing attacks. Furthermore, the proposed method outperforms the state-of-the-art schemes in watermarking characteristics, making it a superior solution to secure medical images in IoMT environments.