Medical Images Encryption Based on Elliptic Curve Cryptography and Chaos Theory

Telecare Medical Information Systems (TMIS) is one of the most important remote technics used for diagnostic and treatment of patients. In this context, the importance of a safe exchange of medical data, comprising signals, images, etc. has received a special attention these recent years. Indeed, as the Digital Imaging and Communications in Medicine (DICOM) objects contain images and linked medical information about the patient, their security and privacy must be addressed seriously. In this framework, many encryption techniques are proposed in the literature to resolve this issue using numerous cryptographic solutions such chaos based theory, elliptic curves cryptography (ECC) and other lightweight solutions. In this paper, we present a comparative study between two encryption approaches namely the ECC and chaos. To the best of our knowledge, it is the first time a comparison between a chaos-based symmetric encryption and EEC based asymmetric encryption is introduced for medical image protection. The performance of the two considered crypto-systems is evaluated in terms of security analysis and execution time. The obtained results are promising and can be used to look further into the exploration of this axis of research.

I. Introduction

The security and privacy of the medical image transmission are one of the critical issues that must be addressed seriously in Telecare Medical Information Systems (TMIS). Image-data transmission from one location to another through an insecure network is usually characterized in terms of privacy, authenticity, integrity and confidentiality. Therefore, more importance must be given to the security of the sensitive data containing in the medical images DICOM. In this context, many solutions are proposed in the literature to overcome this problem using various cryptographic primitives. Recently, Mohamed et al. [1] proposed a chaotic approach based on the 2D-logistic maps, combined with two generators, namely a Linear Congruential Generator (LCG) and Xor Shift Generator (XSG) to produce confusion and diffusion sequences. In 2017, Dolendro et al. [2] suggested to encrypt the medical images by using ElGamal elliptic curves encryption with an efficient way to thwart the stage of data encoding on the used curve.