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Chaos-based encryption of biomedical EEG signals using random quantization technique

As electroencephalography (EEG) signals contain sensitive personal health information, it is generally a legal requirement to prevent their unauthorized access. For example, the HIPAA in the US requires that access to personal health information is limited to properly authorized individuals. In this paper, a chaos-based encryption method is proposed to secure patients' EEG data before transmission over an insecure channel. The proposed method employs a multiplexer to dynamically select between two randomly quantized bitstreams for secure key generation. This method is simulated to encrypt the EEG datasets and the statistical properties such as signal distribution, auto and cross-correlation, power spectral density and the residual deviation of the encrypted/original EEG signals are evaluated. The experimental results verify that the proposed method has high security and is suitable for the protection of sensitive EEG data.