A Proposed Blind DWT-SVD Watermarking Scheme for EEG Data

Abstract

Copyright and integrity violations of digital medical data have become security challenges since the ever-increasing distribution of them between clinical centres and hospitals through the widespread usage of telemedicine, teleradiology, telediagnosis, and teleconsultation. Therefore, preserving authenticity and integrity of medical data including Electroencephalogram (EEG) has become a necessity. Watermark techniques have been thoroughly studied as a means to preserve the authenticity and integrity of the content of medical. Although there is a large volume of works on watermarking and stenography, not many researchers have addressed issues related to EEG data. This paper proposes a new approach that uses discrete wavelet transform (DWT) to decompose EEG signals and singular value decomposition (SVD) to embed watermark into the decomposed EEG signal. Based on the advantage of using the SVD technique, our proposed method achieved blind detection of watermark in which the receiver does not require the original EEG signal to retrieve the watermark. Experimental results show that the proposed EEG watermarking approach maintains the high quality of the EEG signal.