Title :
Wavelet-Based ECG Steganography for Protecting Patient Confidential Information in Point-of-Care Systems
Author :
Ibaida, Ayman ; Khalil, Issa
Author_Institution :
Dept. of Comput. Sci. & Inf. Technol., RMIT Univ., Melbourne, VIC, Australia
Abstract :
With the growing number of aging population and a significant portion of that suffering from cardiac diseases, it is conceivable that remote ECG patient monitoring systems are expected to be widely used as point-of-care (PoC) applications in hospitals around the world. Therefore, huge amount of ECG signal collected by body sensor networks from remote patients at homes will be transmitted along with other physiological readings such as blood pressure, temperature, glucose level, etc., and diagnosed by those remote patient monitoring systems. It is utterly important that patient confidentiality is protected while data are being transmitted over the public network as well as when they are stored in hospital servers used by remote monitoring systems. In this paper, a wavelet-based steganography technique has been introduced which combines encryption and scrambling technique to protect patient confidential data. The proposed method allows ECG signal to hide its corresponding patient confidential data and other physiological information thus guaranteeing the integration between ECG and the rest. To evaluate the effectiveness of the proposed technique on the ECG signal, two distortion measurement metrics have been used: the percentage residual difference and the wavelet weighted PRD. It is found that the proposed technique provides high-security protection for patients data with low (less than 1%) distortion and ECG data remain diagnosable after watermarking (i.e., hiding patient confidential data) and as well as after watermarks (i.e., hidden data) are removed from the watermarked data.
Keywords :
body sensor networks; cryptography; diseases; distortion measurement; electrocardiography; medical signal processing; patient monitoring; steganography; watermarking; wavelet transforms; ECG signal; blood pressure; blood temperature; body sensor networks; cardiac diseases; distortion measurement metrics; encryption; glucose level; patient diagnosis; physiological information; point-of-care systems; public network; remote ECG patient monitoring systems; scrambling technique; watermarked data; wavelet weighted PRD; wavelet-based ECG steganography; Confidentiality; ECG; encryption; steganography; watermarking; wavelet;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2013.2264539