A Novel Lossless Medical Image Encryption Scheme Based on Game Theory With Optimized ROI Parameters and Hidden ROI Position

Jian Zhou,Xiaoqiang Di,Jinqing Li

doi:10.1109/access.2020.3007550

Jian Zhou, Xiaoqiang Di + Show 1 more

Open Access

https://doi.org/10.1109/access.2020.3007550

Copy DOI

Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 43	License type: CC BY 4.0

Affiliation: Changchun University of Science and Technology

Abstract

Medical images contain a large amount of patients' private information. The theft and destruction of medical images will cause irreparable losses to patients and medical institutions. In order to detect the region of interest(ROI) accurately, avoid leakage of ROI position information, and realize lossless recovery of transform domain encryption, we propose a novel lossless medical image encryption scheme based on game theory with optimized ROI parameters and hidden ROI position. In the encryption process, the ROI is a pixel-level transformed to achieve the lossless decryption of medical images and protect medical image information from loss. At the same time, the position information of the ROI is effectively hidden, and leakage of the position information during transmission is avoided. In addition, the quantum cell neural network(QCNN) hyperchaotic system generates random sequence to scramble and diffuse the ROI. Most important of all, the quantitative analysis method of ROI parameters is given, and the optimal balance between encryption speed and encryption security performance is achieved by using game theory. Simulation experiments and numerical analysis verify that the scheme achieves optimized and lossless encryption and decryption of images, and can flexibly and reliably protect the medical images of different types and structures against various attacks.

Highlights

With the rapid development of information and network technology, vast amounts of information are transmitted over networks, information security has received widespread attention [1]–[3]
Digital medical images embed a variety of patient privacy information, and the medical information contained in digital medical images is essential for diagnosis
Inspired by the above motivation, in this paper, we present a novel regions of interest (ROI) optimization lossless medical image encryption and decryption algorithm based on game theory, optimize the ROI parameters, realize the accurate automatic selection of ROI, which can adapt to different types of image formats

Summary

INTRODUCTION

With the rapid development of information and network technology, vast amounts of information are transmitted over networks, information security has received widespread attention [1]–[3]. Inspired by the above motivation, in this paper, we present a novel ROI optimization lossless medical image encryption and decryption algorithm based on game theory, optimize the ROI parameters, realize the accurate automatic selection of ROI, which can adapt to different types of image formats. In the constructing encryption effect set function stage, we mainly analyze the encryption time and security performance of the encryption algorithm with different ROI thresholds In this optimization model, encryption speed, peak signal-to-noise ratio(PSNR), structural similarity(SSIM), and information entropy are used as analysis indexes of encryption effect. This means that the larger the ROI threshold, the fewer image blocks are selected for encryption. LOSSLESS IMAGE SELECTIVE ENCRYPTION/ DECRYPTION SCHEME we give the implementation details of the lossless image selective encryption and decryption scheme

CHAOS KEY GENERATION

DECRYPTION ALGORITHM

ENCRYPTION KEY SPACE ANALYSIS

KEY SENSITIVITY ANALYSIS

SPEED PERFORMANCE

Findings

CONCLUSION