The EEG signals steganography based on wavelet packet transform-singular value decomposition-logistic

Abstract

Brain-computer interface (BCI) technology is widely used in online medicine for the diagnosis and treatment of brain diseases. However, during brain-computer interaction, Electroencephalogram (EEG) signals and private information may be leaked when transmitted through unsecured Internet channels. To protect private information and EEG signal security, this paper proposes a steganography algorithm based on Wavelet Packet Transform-Singular Value Decomposition-Logistic (WPT-SVD-Logistic). The algorithm utilized wavelet packet transform (WPT) to conceal more private information while maintaining better perceptual fidelity. After two-level WPT processing, the EEG signal is decomposed into 4 sub-band signals, and then the singular value decomposition (SVD) method is used to embed private information into these sub-band signals. Additionally, the algorithm employed the Logistic map to confuse private information further and enhance its security. Experimental results show that WPT is more suitable for information hiding in EEG signals. The average peak signal-to-noise ratio of the algorithm on four different datasets is 96.5 dB, indicating that adding private information has a weak impact on the EEG signal. Compared with similar methods, this algorithm has smaller errors and stronger robustness, so it has more potential to become the main means of EEG signal steganography.