Cellular Neural Network-Based Medical Image Encryption
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ORIGINAL RESEARCH
Cellular Neural Network‑Based Medical Image Encryption S. J. Sheela1 · K. V. Suresh1 · Deepaknath Tandur2 · A. Sanjay1 Received: 11 June 2020 / Accepted: 7 October 2020 © Springer Nature Singapore Pte Ltd 2020
Abstract This article introduces a novel cryptosystem for the protection of medical images which is very essential in teleradiology applications. The proposed cryptosystem is based on Fridrich architecture which uses hyperchaotic cellular neural network (CNN) and DNA technology to perform cryptographic operations. In this paper, cellular neural network crumb coding transform (CNN-CCT) is proposed to perform confusion operation. It is used to shuffle the pixel values randomly. The diffusion operation is achieved by employing cipher block chain (CBC) mode of XOR operation which provides greater efficiency in hardware platforms. The diffusion operation is used to change the pixel values, thereby achieving the higher security. Simulation and comparison results infer that the proposed cryptosystem is robust against various cryptographic attacks and competitive with the state-of-the-art encryption schemes. Keywords Teleradiology · Encryption · Chaos · Confusion · Diffusion · Cellular neural network crumb coding transform (CNN-CCT) · CBC
Introduction Telemedicine adopts advanced communication technology to provide sophisticated health care services to remote areas [1]. It is a cost-effective way of providing appropriate diagnosis, treatment planning and prevention diseases through optimal utilization of specialist expertise and services offered by local health care workers. Teleradiology is one of the telehealth services which include X-rays, magnetic resonance imaging (MRI) computerized tomography (CT) etc [2–4]. In eHealth service, the medical images play an important role in the diagnosis, treatment and surgery in almost all diseases. Usually, these images are managed by picture archiving and communication systems (PACS) which * S. J. Sheela [email protected] K. V. Suresh [email protected] Deepaknath Tandur [email protected] 1
Siddaganga Institute of Technology, Visvesvaraya Technological University, Tumakuru, Karnataka 572103, India
Corporate Research India, ABB, Bangalore, Karnataka 560048, India
2
are designed to provide convenient archiving and medical image distribution [5]. However, PACS are usually employed inside an internal hospital network which is protected by a firewall against outside invaders. Further, PACS uses Digital Imaging and Communications in Medicine (DICOM) standard which defines the medical image format and network transport protocol. Each image which is in DICOM format includes patient’s personal data like name, gender, home address, birth date and medical history in the form of small size header file and a huge file with pixel data. Although, PACS and DICOM manages the medical information conveniently and makes eHealth services feasible, but suffers from security threats if the communication extends over the public network [3, 5]. There
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