A proposed blind DWT-SVD watermarking scheme for EEG data

Duy Pham, Dat TRAN, Wanli MA

Research output: A Conference proceeding or a Chapter in BookConference contribution

6 Citations (Scopus)
2 Downloads (Pure)

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.
Original languageEnglish
Title of host publicationInternational Conference on Neural Information Processing (ICONIP 2015)
Subtitle of host publicationLecture notes in computer science
EditorsSabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu
Place of PublicationCham, Switzerland
PublisherSpringer
Pages69-76
Number of pages8
Volume9492
ISBN (Electronic)9783319265612
ISBN (Print)9783319265605
DOIs
Publication statusPublished - 2015
Event22nd International Conference on Neural Information Processing ICONIP 2015 - Istanbul, Istanbul, Turkey
Duration: 9 Nov 201512 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9492
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Neural Information Processing ICONIP 2015
Abbreviated titleICONIP 2015
CountryTurkey
CityIstanbul
Period9/11/1512/11/15

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    Pham, D., TRAN, D., & MA, W. (2015). A proposed blind DWT-SVD watermarking scheme for EEG data. In S. Arik, T. Huang, W. K. Lai, & Q. Liu (Eds.), International Conference on Neural Information Processing (ICONIP 2015): Lecture notes in computer science (Vol. 9492, pp. 69-76). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9492). Springer. https://doi.org/10.1007/978-3-319-26561-2_9