Color image security technique combining encryption and data hiding for healthcare applications.
Authors
Affiliations (4)
Affiliations (4)
- Department of Computer Science & Engineering, National Institute of Technology Patna, Patna, Bihar, India. Electronic address: [email protected].
- Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India. Electronic address: [email protected].
- Department of Computer Science & Engineering, National Institute of Technology Patna, Patna, Bihar, India. Electronic address: [email protected].
- Department of Computer Science and Information Engineering, Asia University, Taichung 413, Taiwan; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan; Symbiosis Centre for Information Technology (SCIT), Symbiosis International University, Pune, India; School of Cybersecurity, Korea University, Seoul, South Korea. Electronic address: [email protected].
Abstract
With the rapid growth of internet technologies, the transmission and storage of multimedia data have become increasingly convenient. However, digital images, especially in the healthcare domain, are often more popular and sensitive information carriers than other forms of multimedia and plain-text reports. The security of medical information has become a critical issue. To address this challenge, we propose a color (in the YCbCr color space) medical image security technique combining encryption and data hiding with usability through thumbnail preservation. Our method introduces four key innovations. First, a novel cascading key is generated using deep learning for image encryption; second, the sensitive chrominance information portion of the medical image is encrypted using a highly secure key, reducing the overall time cost while simultaneously securing the images; third, confidential information is concealed in significant chrominance portion of the color medical images to obtain stego images, substantially preventing potential copyright violations. Finally, thumbnail-preserving encryption (TPE) is applied to the luminance portion to effectively preserve confidentiality and availability. Extensive experiments on two standard medical datasets demonstrate the effectiveness of the proposed method. Our key generation approach achieves a high level of unpredictability and a large key space, along with strong data-hiding and TPE performance with respect to robustness and availability analysis, respectively. These features make it particularly suitable for secure healthcare applications.