Medical identity theft in telemedicine: solving the privacy and security issues

• Main Authors: Olanrewaju, Rashidah Funke, Khalifa, Othman Omran
• Format: Monograph
• Language: English
• Published: IIUM Press 2015
• Subjects: Q Science (General); R Medicine (General)
• Online Access: http://irep.iium.edu.my/45556/1/45556_Medical%20identity%20theft%20in%20telemedicine%20-%20Monograph.pdf; http://irep.iium.edu.my/45556/
• Institution: Universiti Islam Antarabangsa Malaysia

Medical Identity Theft (MIDT) occurs when fraudsters impersonate unsuspecting individuals to obtain medical care, buy drugs, and submit fake billings or altered medical records. The consequences can sometimes be life-threatening if wrong information ends up in the victim’s personal medical records. With advancement in telecommunication combined with improved information infrastructures that has opened up new dimensions in e-health/telemedine environment, the risks are expected to increase, since electronic medical records has become even more prevalent and pervasive. Such technologies make it easy to access, store, manipulate and replicate medical information and images. Although these technologies help reduce the time and effort in diagnoses and treatment at lower cost. However protection and authentication of such medical information and images are now becoming increasingly important in telemedicine environment where images and medical information are readily distributed over electronic networks. Intruders/hackers may gain access to confidential information and possible alter such vital records. As such, the vulnerability associated with data over the internet needs to be eliminated. This is because any alteration to medical information may cause a devastating effect to the patient. In this work, a digital watermarking that detects any attempt of altering patient data is proposed. The discrete wavelet transform of the 8 x 8 non-overlapping blocks of the medical test image is generated prior to the embedding process. 64-bits binary equivalent of digit numbers representing patient’s entry date and file ID used as the watermark is embedded inside the corresponding patient’s medical image by quantizing the coefficient of the highest frequency components of each block. An average of 80dB Peak Signal to Noise Ratio (PSNR) was achieved after watermarking which show that the watermark is highly imperceptible . The findings of this study also showed that the extracted watermark compared with the original watermark was able to authenticate if the image was tampered or not. Hence, the proposed algorithm enables quick and excellent detection capability of any modification done to the medical images.