An introduction to signal detection and estimation (2nd ed.)
An introduction to signal detection and estimation (2nd ed.)
Signals & systems (2nd ed.)
Cryptanalysis of Discrete-Sequence Spread Spectrum Watermarks
IH '02 Revised Papers from the 5th International Workshop on Information Hiding
Rights protection for relational data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
On the Privacy Preserving Properties of Random Data Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Privacy-preserving k-means clustering over vertically partitioned data
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy and Ownership Preserving of Outsourced Medical Data
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Wavelet Transformation Based Watermarking Technique for Human Electrocardiogram (ECG)
Journal of Medical Systems
Rights Protection for Discrete Numeric Streams
IEEE Transactions on Knowledge and Data Engineering
The Applicability of the Perturbation Model-based Privacy Preserving Data Mining for Real-world Data
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Watermarking relational databases
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Watermarking medical signals for telemedicine
IEEE Transactions on Information Technology in Biomedicine
Secure spread spectrum watermarking for multimedia
IEEE Transactions on Image Processing
Secure information embedding into 1D biomedical signals based on SPIHT
Journal of Biomedical Informatics
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Due to the recent explosion of `identity theft' cases, the safeguarding of private data has been the focus of many scientific efforts. Medical data contain a number of sensitive attributes, whose access the rightful owner would ideally like to disclose only to authorized personnel. One way of providing limited access to sensitive data is through means of encryption. In this work we follow a different path, by proposing the fusion of the sensitive metadata within the medical data. Our work is focused on medical time-series signals and in particular on Electrocardiograms (ECG). We present techniques that allow the embedding and retrieval of sensitive numerical data, such as the patient's social security number or birth date, within the medical signal. The proposed technique not only allows the effective hiding of the sensitive metadata within the signal itself, but it additionally provides a way of authenticating the data ownership or providing assurances about the origin of the data. Our methodology builds upon watermarking notions, and presents the following desirable characteristics: (a) it does not distort important ECG characteristics, which are essential for proper medical diagnosis, (b) it allows not only the embedding but also the efficient retrieval of the embedded data, (c) it provides resilience and fault tolerance by employing multistage watermarks (both robust and fragile). Our experiments on real ECG data indicate the viability of the proposed scheme.