Crypto-watermarking scheme for tamper detection of medical images

ABSTRACT

Medical images of patients are often exchanged among specialist physicians, radiologists, hospital authorities and patients for remote monitoring and assessment as part of telemedicine. With the revolutions in the technology, the threat models and attackers are evolving on a daily basis and hence there is a constant need for the development of novel schemes that can protect personal information. In this paper, a non-blind fragile watermarking is developed to invisibly hide and integrate patient’s unique information such as biometrics in their radiological images for secure authentication, integrity verification and tamper detection purposes. The concept of compressive sensing theory is employed with discrete cosine transform to improve confidentiality. The performance of the proposed scheme is tested and evaluated on three types of medical images: X-ray, computed tomography and magnetic resonance imaging. The proposed scheme presents a means of verifying data integrity when medical images are subjected to attacks. The experimental results showed that the scheme invisibly hides high payloads of patient’s unique identities, apart from providing better tamper detection. The simulation results show that the proposed scheme provides high imperceptibility up to 92 dB and high payload capacity of up to 1 bpp.

KEYWORDS:

• Discrete Cosine Transform (DCT)
• Compressive Sensing (CS)
• cryptography
• medical image
• watermarking
• telemedicine

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research work is funded (GRD-608) by the Karnataka Science and Technology Promotion Society, Department of Information Technology, Bio Technology and Science & Technology, Government of Karnataka, India under the category of Seed Money for Young Scientist Research (SMYSR), Vision Group of Science and Technology (VGST) Scheme.

Notes on contributors

Surekha Borra

Surekha Borra received her Ph.D. in Electronics and Communication Engineering in 2015. She is a professor in Electronics and Communication Engineering Department, K. S. Institute of Technology, Bangalore, India. Her areas of research interests include digital watermarking, biometrics ecurity, machine learning, video analytics and image processing.

Rohit Thanki

Rohit Thanki received his Ph.D. in Electronics and Communication Engineering in 2017. He received B.E. and M.E. in Electronics and Communication Engineering in 2008 and 2010, respectively. His research areas of interests are multimedia security, watermarking, CS, medical image nalysis, machine learning, deep learning, biometrics and advanced computing.