EiMOL: A Secure Medical Image Encryption Algorithm based on Optimization and the Lorenz System

Abstract

Nowadays, the demand for digital images from different intelligent devices and sensors has dramatically increased in smart healthcare. Due to advanced low-cost and easily available tools and software, manipulation of these images is an easy task. Thus, the security of digital images is a serious challenge for the content owners, healthcare communities and researchers against illegal access and fraudulent usage. In this paper, a secure medical image encryption algorithm, EiMOL , based on optimization and the Lorenz system, is proposed for smart healthcare applications. In the first stage, an optimized random sequence (ORS) is generated through directed weighted complex network particle swarm optimization using the genetic algorithm (GDWCN-PSO). This random number matrix and the Lorenz system are adopted to encrypt plain medical images, obtaining the cipher messages with a relationship to the plain images. According to our obtained results, the proposed EiMOL encryption algorithm is effective and resistant to the many attacks on benchmark Kaggle and Open-i datasets. Further, extensive experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art approaches.

Novel data encryption scheme and its application to secure multi-party communication

“…The latter hides the image content to be protected into a complex and large subset of the information space, making it impossible for attackers to discover whether and where the information is hidden, thus reducing the chance of information stealing by attackers. Meanwhile, image encryption algorithms by combining chaos theory [1][2][3], cellular automata, DNA coding [4], optical transformation [5], compressive sensing (CS), and other related techniques have been proposed. For example, Ye et al proposed an efficient symmetric image encryption algorithm using intertwining logistic chaotic map [6] to address the issue of low plain image sensitivity.…”

An algorithm based on 6D fractional order hyperchaotic system and knight tour algorithm to encrypt image

“…Furthermore, Lorenz system encrypts general medical images. This algorithm is resistant to attacks in many ways, such as benchmark Kaggle and Open-i datasets [25]. Alexan W et al used fractional order four-dimensional dynamic Chen system to encrypt multilayer color image cryptosystems.…”

MieWC: Medical image encryption using wavelet transform and multiple chaotic maps

“…12,13 It is the process of transforming information or data to non-informative data or data with different information to prevent unauthorized users from acquiring the original information. [14][15][16] Lately, many researchers have developed encryption methods for digital images. The authors of Reference 16 have proposed a combination of RDWT and RSVD to generate an encryption key.…”

“…Among the different data security schemes, encryption is an effective tool that is intended as a solution to the issues of copyright protection and authentication of digital images 12,13 . It is the process of transforming information or data to non‐informative data or data with different information to prevent unauthorized users from acquiring the original information 14–16 …”

“…Further, it has a very high time complexity for the overall process. The authors of Reference 14 have proposed a technique using a logistic map and 3D‐LS. An optimized random sequence is generated using GDWCN‐PSO and a logistic map, which is used for the shuffling process.…”