Electronic healthcare (e-health) networks are increasingly popular, particular during pandemics such as COVID-19. This reinforces the importance of ensuring security and privacy for data-in-transit. One such solution is steganography-based schemes that utilize biological signals (e.g., ECG) as cover signals to preserve the privacy of patient personal information without affecting the diagnostic features. There are various limitations in existing steganography-based schemes, and in this study we present an effective privacy protection scheme leveraging both multidimensional steganography and shared keys. To enhance security and accelerate signal processing in our design, the Fast Walsh-Hadamard transform (FWHT) is employed to decompose ECG signals into a set of coefficients, of which the less-significant coefficients are used to construct the multidimensional space. The negotiated shared keys facilitate the embedding of encrypted data in the constructed space. We then evaluate the proposed scheme using different categories of ECG signals in the MIT-BIH database. It is observed that the signal distortion is minimal (i.e., less than 1%), even if the embedded data reaches the maximum embedding capacity. The security analysis also demonstrates that unauthorized retrieval of hidden information is not practical, within a short period of time.

中文翻译：

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SIP：一种高效安全的电子健康网络信息传播方案

电子医疗保健 (e-health) 网络越来越受欢迎，尤其是在 COVID-19 等大流行期间。这强调了确保传输中数据的安全性和隐私性的重要性。一种这样的解决方案是基于隐写术的方案，该方案利用生物信号（例如，ECG）作为覆盖信号来保护患者个人信息的隐私而不影响诊断特征。现有的基于隐写术的方案存在各种局限性，在本研究中，我们提出了一种利用多维隐写术和共享密钥的有效隐私保护方案。为了在我们的设计中增强安全性并加速信号处理，我们采用了快速 Walsh-Hadamard 变换 (FWHT) 将 ECG 信号分解为一组系数，其中较不显着的系数用于构造多维空间。协商的共享密钥促进了加密数据在构造空间中的嵌入。然后，我们使用 MIT-BIH 数据库中不同类别的 ECG 信号评估所提出的方案。可以观察到，即使嵌入的数据达到最大嵌入容量，信号失真也是最小的（即小于 1%）。安全分析还表明，在短时间内未经授权检索隐藏信息是不切实际的。小于 1%），即使嵌入的数据达到最大嵌入容量。安全分析还表明，在短时间内未经授权检索隐藏信息是不切实际的。小于 1%），即使嵌入的数据达到最大嵌入容量。安全分析还表明，在短时间内未经授权检索隐藏信息是不切实际的。