The health Internet of Things (IoT) lays the basis for emergency care for epileptic patients. The security of data transmission in the network calls for a robust monitoring technique. This paper proposes a monitoring model for epileptic patients, using a cloud-based health IoT system. To ensure the data security, watermarking was carried out through discrete wavelet transform-singular value decomposition (DWT-SVD), followed by short time Fourier transform (STFT). The proposed watermarking scheme, which is based on STFT and DWT-SVD, was verified on electroencephalography (EEG) data of class Z and class S. The results show that our scheme achieved a good watermarking performance, with a peak signal-to-noise ratio (PSNR) of 35.25 and a signal-to-noise ratio (SNR) of 31.32.
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Gupta et al. (2019) studied this question.