Medical Image Encryption Algorithm Research Articles

Memristive Hopfield neural network with multiple controllable nonlinear offset behaviors and its medical encryption application

Memristors possess inherent nonlinearity and synaptic attributes, rendering them more suited for integration as synapses within neural networks compared to resistors. Furthermore, their utilization induces significant alterations in the dynamic behavior of neural networks, hence bestowing considerable value in the realm of secure communication applications. In this paper, an improved cosine memristor is proposed, three representative memristor Hopfield neural networks (MHNNs) are constructed using it as synapse. The MHNNs exhibit rich initial offset boost behaviors, we summarize these phenomena into four types based on the offset characteristics. In particular, these offset types can be converted by adjusting internal parameters of the memristor. In addition, the MHNNs are constructed and tested using both software and hardware components, validating the accuracy of theoretical simulation and the implementation of systems. Ultimately, a set of bit-plane level medical image encryption algorithm is proposed on the basis of MHNNs, which has excellent encryption performance and can effectively protect the privacy of patients.

Real time hybrid medical image encryption algorithm combining memristor-based chaos with DNA coding

Image encryption is a commonly used method to secure medical data on a public network, playing a crucial role in the healthcare industry. Because of their complex dynamics, memristors are often used in developing novel chaotic systems that can improve the efficiency of encryption algorithms based on chaos. In this work, we propose a novel locally active memristor-based chaotic circuit model and present a real time hybrid image encryption application developed on a PYNQ-Z1 (Python Productivity for Zynq) low-cost FPGA board using Jupiter programming environment. The proposed hybrid algorithm combines memristor-based chaos with a DNA (deoxyribonucleic acid) encryption algorithm exploiting diffusion-confusion technique. We initially present a new compact and inductorless chaotic circuit, derive the model equations, and then verify its chaotic dynamics numerically through the investigation of the phase portraits, Lyapunov exponents and the bifurcation diagrams. We further implement the chaotic circuit experimentally with discrete elements. The randomness of the chaotic sequence is improved using Trivium and von Neumann post-processor algorithms and assessed through the NIST tests. Finally, the performance of the encryption algorithm is evaluated through various metrics, including histogram and correlation analyses, differential attack, information entropy, as well as data-loss and noise attack, demonstrating its security and suitability for real-time encryption systems.

3D medical image encryption algorithm using biometric key and cubic S-box

Considering the scarcity of research on 3D medical image encryption, this paper proposes a novel 3D medical image encryption scheme based on biometric key and cubic S-box. To enhance the data security, biometric keys are utilized to overcome the limitations of traditional methods where secret keys with no practical meaning, fixed length, and finite key space, while cubic S-box is constructed to increase the nonlinearity of image cryptosystem. The proposed cryptosystem mainly consists of four phases: pseudo-random sequence generation, confusion, substitution, and diffusion. Firstly, the stepwise iterative algorithm based on coupled chaotic systems is utilized for generating pseudo-random sequences for confusion and diffusion. Secondly, the confusion algorithm based on multiple sorting can scramble pixel positions in 3D images. Thirdly, guided by the designed cubic S-box, pixel substitution is executed sequentially. Lastly, the diffusion algorithm based on ECA and finite field multiplication is capable of increasing the plaintext sensitivity of cryptosystem by concealing the statistical characteristics of plaintext. Simulation experiments performed on multiple 3D medical images demonstrate that the proposed encryption scheme exhibits favorable statistical performance, sufficiently large key space, strong system sensitivity and robustness, and can resist various typical cryptographic attacks.

Multiuser medical image encryption algorithm using phase-only CGH in the gyrator domain.

In this paper, a multiuser medical image encryption algorithm is proposed. The proposed algorithm utilizes polar decomposition, which enables multiuser features in the proposed algorithm. A computer-generated hologram (CGH) improves the security of the proposed algorithm in the gyrator domain. The phase-only CGH-based multiuser algorithm offers advantages such as storing a large amount of information in a compact space, resistance to counterfeiting, and enhanced security. The proposed method is validated with various statistical metrics, such as information entropy, mean squared error, correlation coefficient, histogram, and mesh plots. Results confirm that the proposed algorithm is secure and robust against potential attacks, such as plaintext attacks, iterative attacks, and contamination attacks. The proposed method has a large keyspace, which makes it very difficult to be breached in real-time with existing computational power.

Medical image encryption algorithm based on a new five-dimensional multi-band multi-wing chaotic system and QR decomposition

In this study, we propose a medical image encryption algorithm based on a new five-dimensional (5D) multi-band multi-wing chaotic system and QR decomposition. First, we construct a new 5D multi-band multi-wing chaotic system through feedback control, which has a relatively large Lyapunov exponent. Second, we decompose the plaintext image matrix and chaotic sequence into an orthogonal matrix and upper triangular matrix using QR decomposition. We multiply the orthogonal matrix decomposed from the original image by the orthogonal matrix decomposed from the chaotic sequence. In this process, we use the chaotic sequence to control left and right multiplication. Simultaneously, we chaotically rearrange the elements in the upper triangular matrix using the improved Joseph loop and then multiply the two resulting matrices. Finally, we subject the product matrix to bit-level scrambling. From the theoretical analysis and simulation results, we observed that the key space of this method was relatively large, the key sensitivity was relatively strong, it resisted attacks of statistical analysis and gray value analysis well, and it had a good encryption effect for medical images.

Novel substitution-box generation using group theory for secure medical image encryption in E-healthcare

<abstract> <p>With the increasing need for secure transmission and storage of medical images, the development of robust encryption algorithms is of paramount importance. Securing sensitive digital medical imagery information during transmission has emerged as a critical priority in the e-Healthcare systems. Recent research has highlighted the significance of developing advanced medical image encryption algorithms to ensure secure transmission during telediagnosis and teleconsultations. In this study, we propose a novel medical image encryption algorithm which is based on a novel substitution-box generation algebraic method using a combination of a multiplicative cyclic group with an order of 256 and a permutation group with a large order. To evaluate the security performance of the proposed generated S-box, various standard security indicators are assessed and analyzed. The newly proposed medical image encryption algorithm utilizes the generated S-box, along with bit-plane slicing, circular shifting, and XOR operations, to achieve enhanced security and robustness for encrypting sensitive imagery data. In order to assess the effectiveness of the proposed encryption algorithm, a comprehensive benchmarking analyses, specifically designed for evaluating image encryption schemes, have been conducted. The results obtained from the comparison and other analyses serve to validate the optimal features and high cryptographic strength exhibited by the proposed method. Hence, the proposed algorithm demonstrates significant effectiveness and holds considerable promise in the realm of medical image encryption for secure e-Healthcare systems.</p> </abstract>

An efficient medical image encryption algorithm for telemedicine applications

Applications for healthcare execute computations that support various patient diagnostics and save private user data on cloud servers. User data is being held at ransom as a result of increasing cyberattacks on medical systems. Additionally, unreliable external parties who sell private data for profit can access mathematical calculations on data stored in the cloud. In this research, we suggest an efficient Homomorphic medical image encryption algorithm protecting medical plaintext data against unauthorised access via homomorphic encryption. To increase the security level Paillier's encryption scheme (PES) is utilized to select the optimal key. Homomorphic encryption is a method of authentication which helps one to perform observes of the encrypted information through decrypting it. Secret sharing splits up computations among a number of edge virtual nodes and hides all arithmetic operations, preventing unreliable cloud servers from figuring out what was done with the encrypted patient data. Cloud computing resources help virtual edge nodes perform computationally difficult mathematical operations and lower latency in device-edge node data transmission. During the experimental study, different factors including execution time, encryption time, and decryption time are used to evaluate the performance of the suggested approach. The proposed technique's execution time is 2% faster than the currently used HE method and 4% faster than the ECC algorithm.

A variable dimensional chaotic map-based medical image encryption algorithm with multi-mode.

Since the COVID-19 pandemic, telemedicine or non-face-to-face medicine has increased significantly. In practice, various types of medical images are essential to achieve effective telemedicine. Medical image encryption algorithms play an irreplaceable role in the fast and secure transmission and storage of these medical images. However, most of the existing medical image encryption algorithms are full encryption algorithms, which are inefficient and time-consuming, so they are not suitable for emergency medical scenarios. To improve the efficiency of encryption, a small number of works have focused on partial or selective encryption algorithms for medical images, in which different levels of encryption strategies were adopted for different information content regions of medical images. However, these encryption algorithms have inadequate security more or less. In this paper, based on the Logistic map, we designed an improved variable dimension map. Then, an encryption algorithm for medical images was proposed based on it. This algorithm has two modes: (1) full encryption mode and (2) semi-full encryption mode, which can better adapt to different medical scenarios, respectively. In full encryption mode, all pixels of medical images are encrypted by using the confusion-diffusion structure. In semi-full encryption mode, the region of interest of medical images is extracted. The confusion was first adopted to encrypt the region of interest, and then, the diffusion was adopted to encrypt the entire image. In addition, no matter which encryption mode is used, the algorithm provides the function of medical image integrity verification. The proposed algorithm was simulated and analyzed to evaluate its effectiveness. The results show that in semi-full encryption mode, the algorithm has good security performance and lower time consumption; while in full encryption mode, the algorithm has better security performance and is acceptable in time.

Selective region medical image encryption algorithm based on cascade chaos and two-dimensional Joseph traversal

Aiming at the problem that medical image information is easy to be stolen, tampered and maliciously destroyed in the transmission process, a selective region medical image encryption algorithm based on cascade chaos is proposed. The encryption algorithm consists of two stages: region of interest (ROI) encryption and full image encryption. First, the Cubic map is cascaded with an improved Cosine map. Through the analysis of dynamic characteristics, the cascade map has better chaotic performance than the traditional chaotic systems. The key sequence is generated by the cascade map and the image. Then edge detection is performed on the image to determine ROI. ROI is divided into multiple image blocks, and a new gradient algorithm is used to label the sub-blocks containing important information. A modified two-dimensional Joseph traversal method is used to scramble the positions of pixels in each sub-block, and further modify their pixel values with a round of diffusion. Finally, we use a block V-shape scrambling method to scramble the entire image. The final encrypted image is obtained through a round of bidirectional diffusion of all pixels using chaotic sequences. Simulation results and security analysis show that the algorithm has large key space and sufficient security. It can effectively resist various malicious attacks.

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

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 article, 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.

Atrial fibrillation medical image encryption algorithm based on deep learning and adaptive block

Atrial fibrillation medical image encryption algorithm based on deep learning and adaptive block

Atrial fibrillation medical image encryption algorithm based on deep learning and adaptive block

Atrial fibrillation medical image encryption algorithm based on deep learning and adaptive block

A one-round medical image encryption algorithm based on a combined chaotic key generator.

Medical images of patients must be securely transmitted and kept private in telemedicine. To secure such medical images, this paper proposes a single round chaotic image encryption scheme based on a permutation-diffusion structure. A combined chaotic key generator (CCKG) is proposed to enhance key sensitivity and generation in order to improve the security of medical images to be encrypted. CCKG is used to produce the initial seeds for the fractional order chaotic system (FOCS) and Lorenz system (LS) for the permutation and diffusion processes, respectively. CCKG together with proposed permutation and diffusion methods enhances cipher image security in single round. Using zigzag transform (ZT) scanning, the plain image is first permuted block by block. The type of scanning used on each block is heavily influenced by the ZT selection from FOCS and LS. Following block-wise permutation, the permutation order (PO) generated from LS performs overall permutation. Based on the pixel positions, the overall permuted image is divided into odd and even parts. Then these parts of the images are diffused separately by the random pixel matrices generated by LS and FOCS. The cipher image is formed by combining the odd and even parts after diffusion. Secret key analysis, statistical analysis, differential attack analysis, and simulations confirm that with a single round of image encryption, the proposed system is competent, robust and effective.

Multiple medical image encryption algorithm based on scrambling of region of interest and diffusion of odd-even interleaved points

Due to the security requirement brought by the rapid development of electronic medical, this paper proposes an encryption algorithm for multiple medical images. The algorithm can not only encrypt grayscale medical images of any number and any size at the same time, but also has good encryption effect when applied to color images. Considering the characteristics of medical images, we design an encryption algorithm based on the region of interest (ROI). Firstly, extract the region of interest of the plaintext images and obtain the coordinates, calculate the hash value of the large image composed of all plaintext images. Set the coordinates and hash value as the secret key. This operation makes the whole encryption algorithm closely related to the plaintext images, which greatly enhances the ability to resist chosen plaintext attacks and improves security of the algorithm. In the process of encryption, chaotic sequences generated by Logistic-Tent chaotic system (LTS) are used to perform two scrambling and one diffusion, that is, pixel swapping based on the region of interest, Fisher-Yates scrambling and our newly proposed diffusion algorithm based on odd–even interleaved points. After testing and performance analysis, the algorithm can achieve good encryption effect, can resist various attacks, and has a higher security level and faster encryption speed.

A plain-image correlative semi-selective medical image encryption algorithm using enhanced 2D-logistic map.

Modern medical examinations have produced a large number of medical images. It is a great challenge to transmit and store them quickly and securely. Existing solutions mainly use medical image encryption algorithms, but these encryption algorithms, which were developed for ordinary images, are time-consuming and must cope with insufficient security considerations when encrypting medical images. Compared with ordinary images, medical images can be divided into the region of interest and the region of background. In this paper, based on this characteristic, a plain-image correlative semi-selective medical image encryption algorithm using the enhanced two dimensional Logistic map was proposed. First, the region of interest of a plain medical image is permuted at the pixel level, then for the whole medical image, substitution is performed pixel by pixel. An ideal compromise between encryption speed and security can be achieved by full-encrypting the region of interest and semi-encrypting the region of background. Several main types of medical images and some normal images were selected as the samples for simulation, and main image cryptanalysis methods were used to analyze the results. The results showed that the cipher-images have a good visual quality, high information entropy, low correlation between adjacent pixels, as well as uniformly distribute histogram. The algorithm is sensitive to the initial key and plain-image, and has a large keyspace and low time complexity. The time complexity is lower when compared with the current medical image full encryption algorithm, and the security performance is better when compared with the current medical image selective encryption algorithm.

Medical image encryption algorithm based on hyper‐chaotic system and DNA coding

With the international development of the medical service informatisation, medical information sharing has become the key standard to measure the degree of medical informatisation. In this process, it is important to ensure the security of patients' medical information such as patients' records, examination reports, images and so on. In this article, an image encryption scheme based on Secure Hash Algorithm 3 (SHA-3), DNA coding and high dimensional chaos system is proposed to promote the security level of medical images in information sharing processes such as over the network. First, SHA-3 algorithm is used to calculate the hash value of the input image, and the result is taken as the initial value of the hyper-chaotic system. Second, the intensity value of the input image is converted into a serial binary digital stream. Third, the pseudo-random sequence generated by a 4-dimensional hyper-chaotic system is used to perturb the bit stream globally so as to achieve the purpose of hiding the effective information of the input image. During the operation of hyper-chaotic sequence and DNA sequence, algebraic and complementary operations are performed on DNA encoding values to enhance encryption performance. Finally, simulations have been applied on an open-source medical image database, and the results demonstrate obvious encryption effectiveness and high security level of the proposed encryption algorithm in the robustness of noise and clipping attacks.

FastMIE: Faster medical image encryption without compromising security

In the Internet age, medical image security is very important in the field of e-healthcare. Several encryption algorithms have been developed, but they either do not achieve high security or they are computationally overhead for medical images, and thus may not be suitable for e-healthcare applications. In this paper, we develop a medical image encryption algorithm, namely FastMIE, that can provide security at low computational time. To achieve high security, we encrypt the segmented part of the image by using a key generated by redundant-discrete wavelet transform (RDWT) and randomized-singular value decomposition (RSVD) and scrambled segmented image. To reduce the computational cost, we encrypt only the significant part of the original-image instead of considering the whole image. Compared with the existing works, our FastMIE takes much less time in encrypting and has a greater ability of securing the image.

A Novel Medical Image Encryption Using R鰏sler System

The technological advances made possible by the Internet, coupled with the unforeseen critical circumstances set in motion by the Covid-19 pandemic, have greatly increased the generation and transmission of medical images every day. Medical image transmission over an unsecured public network threatens the privacy of sensitive patient information. We have, in this paper, designed a new secure color medical image encryption algorithm based on binary plane decomposition, DNA (deoxyribonucleic acid) computing, and the chaotic Rössler dynamical system. At first, a bit-by-bit swap is performed on twenty four binary planes of the input image and encoded using DNA encoding rules. Thereafter, the Rössler system is used to modify the pixel values of the encoded image, which is subsequently decoded. Finally, the ciphered image is obtained by pixel-by-pixel permutation using position sequences. An innovative approach is used to compute keys from the color components of the input image. Extensive performance experiments of the proposed technique is conducted with metrics such as key sensitivity, key space, correlation coefficients (horizontal, diagonal and vertical directions), histograms, information entropy, number of pixel changes rate (NPCR), information entropy, unified average changing intensity (UACI), and encryption time. Comparative analyses have demonstrated that the proposed algorithm is fast, robust and competitive.

Multi-Objective Evolution of Strong S-Boxes Using Non-Dominated Sorting Genetic Algorithm-II and Chaos for Secure Telemedicine

There exist several performance criteria for cryptographically strong substitution boxes which are often conflicting with each other. Constructing S-boxes that satisfy multiple criteria with optimal tradeoffs is one of the challenging tasks for cryptographers. In practice, the existing S-box designing algorithms are used to optimize only a single performance criterion, mainly the nonlinearity, which usually resulted in weak scores of other equally significant criteria. To overcome this problem, a multi-objective optimization based method is presented in this paper which constructs 8×8 S-boxes satisfying multiple criteria of balancedness, high nonlinearity, low differential uniformity, and low auto-correlation. The fulfillment of multiple objectives is done by applying the chaos-assisted non-dominated sorting genetic algorithm-II to evolve S-boxes. The performance assessment of a proposed method and comparative analysis with available optimization based and other state-of-the art algorithms demonstrate its proficiency to generate significantly better S-box solutions with good Pareto-optimal security features. Eventually, the S-boxes with minimum NL of 110, DU as low as 8, and ACF as low as 80, are obtained after the optimization. Furthermore, the obtained Pareto-optimal S-box is utilized to put forward a medical image encryption algorithm for secure telemedicine services. The suggested encryption algorithm makes use of S-box for performing the required permutation and diffusion of images. The encryption performance assessment and comparison analyses validate its effectiveness for securing medical imagery data in telemedicine networks.

Medical image encryption algorithm based on a new five-dimensional three-leaf chaotic system and genetic operation.

Current image encryption methods have many shortcomings for the medical image encryption with high resolution, strong correlation and large storage space, and it is difficult to obtain reliable clinically applicable medical images. Therefore, this paper proposes a medical image encryption algorithm based on a new five-dimensional three-leaf chaotic system and genetic operation. And the dynamic analysis of the phase diagram and bifurcation diagram of the five-dimensional three-leaf chaotic system selected in this paper is carried out, and NIST is used to test the randomness of its chaotic sequence. This algorithm follows the diffusion-scrambling framework, especially using the principle of DNA recombination combined with the five-dimensional three-leaf chaotic system to generate a chaotic matrix that participates in the operation. The bit-level DNA mutation operation is introduced in the diffusion, and the scrambling and diffusion effects have been further improved. Algorithm security and randomness have been enhanced. This paper evaluates the efficiency of this algorithm for medical image encryption in terms of security analysis and time performance. Security analysis is carried out from key space, information entropy, histogram, similarity between decrypted image and original image, PSNR, correlation, sensitivity, noise attack, cropping attack and so on. Perform time efficiency analysis from the perspective of time performance. The comparison between this algorithm and the experimental results obtained by some of the latest medical image encryption algorithms shows that this algorithm is superior to the existing medical image encryption algorithms to a certain extent in terms of security and time efficiency.