A Scheme for Image Encryption And Decryption of Chaotic System Based on memristors

Chaos and compressive sensing based novel image encryption scheme

Medical images demand robust privacy protection, driving research into advanced image encryption (IE) schemes. However, current IE schemes still encounter certain challenges in both security and efficiency. Fractional-order Hopfield neural networks (HNNs) demonstrate unique advantages in IE. The introduction of fractional-order calculus operators enables them to possess more complex dynamical behaviors, creating more random and unpredictable keystreams. To enhance privacy protection, this paper introduces a high-performance medical IE scheme that integrates a novel 4D fractional-order HNN with a differentiated encryption strategy (MIES-FHNN-DE). Specifically, MIES-FHNN-DE leverages this 4D fractional-order HNN alongside a 2D hyperchaotic map to generate keystreams collaboratively. This design not only capitalizes on the 4D fractional-order HNN’s intricate dynamics but also sidesteps the efficiency constraints of recent IE schemes. Moreover, MIES-FHNN-DE boosts encryption efficiency through pixel bit splitting and weighted accumulation, ensuring robust security. Rigorous evaluations confirm that MIES-FHNN-DE delivers cutting-edge security performance. It features a large key space (2383), exceptional key sensitivity, extremely low ciphertext pixel correlations (<0.002), excellent ciphertext entropy values (>7.999 bits), uniform ciphertext pixel distributions, outstanding resistance to differential attacks (with average NPCR and UACI values of 99.6096% and 33.4638%, respectively), and remarkable robustness against data loss. Most importantly, MIES-FHNN-DE achieves an average encryption rate as high as 102.5623 Mbps. Compared with recent leading counterparts, MIES-FHNN-DE better meets the privacy protection demands for medical images in emerging fields like medical intelligent analysis and medical cloud services.

In this chapter, the great sensitivity of nonlinear systems, and especially of chaotic systems, on the initial conditions and on the variation of their parameters, was used to design a novel image encryption scheme. Until now, a great number of chaotic autonomous continuous systems or discrete dynamical systems, have been used in various image encryption processes, as a source of random numbers. However, in this work, a Chaotic Random Bit Generator (CRBG), which is based on a non-autonomous dynamical system, is used. For ridding from the system the influence of the external source and increasing the security of the proposed generator, the Poincar\(\acute{e}\) section for sampling the signal has been used. As a dynamical system, the very well-known Duffing–van der Pol system has been chosen, presenting very good statistical results. The aforementioned CRBG is the “heart” of the proposed image encryption scheme. Finally, the security analysis of the proposed encryption scheme, based on histogram analysis, correlation of two adjacent pixels, differential analysis and information entropy, demonstrate the robustness of the proposed chaotic encryption scheme against all kinds of statistical, cryptanalytic, and brute-force attacks.

Dynamic 3D scrambled image based RGB image encryption scheme using hyperchaotic system and DNA encoding

PurposeThe ammeter can measure the direct current and low-frequency alternating current through the wires, but it is difficult to measure complex waveforms. The oscilloscope can measure complex waveforms, but it is easy to measure the voltage waveform and difficult to measure the current waveform. Thus, how to measure complex current waveforms with oscilloscope is an important and crucial issue that needs to be solved in practical engineering applications. To solve the above problems, an active short circuit line method is proposed to measure the volt-ampere characteristic curve of chaotic circuits.Design/methodology/approachIn this paper, an active short circuit line method is proposed to measure the volt-ampere characteristic curve of various chaotic circuits especially for memristive systems. A memristor-based chaotic system is introduced, and the corresponding memristor-based circuit is constructed and implemented by using electronic components.FindingsThe chaotic attractors and volt-ampere characteristic curve of the memristor-based chaotic circuit are successfully analyzed and verified by oscilloscope measurement with the proposed active short circuit line method. Accordingly, the hardware circuit experiments are carried out to validate the effectiveness and feasibility of the active short circuit line method for these chaotic circuits. A good agreement is shown between the numerical simulations and the experimental results.Originality/valueThe primary contributions of this paper are as follows: an active short circuit line method for measuring the volt-ampere characteristic curve of chaotic circuits is proposed for the first time. A memristor-based chaotic system is also constructed by using memristor as nonlinear term. Then, the active short circuit line method is applied to measure the volt-ampere characteristic curve of the corresponding memristor-based chaotic circuit.

Image encryption has emerged as a method of disguising an image with a noisy or meaningless appearance to prevent its content from being accessed by unauthorized users. We propose an architecture named flexible image encryption and decryption ResNet (FEDResNet) for diffusing an image in end-to-end mode. The architecture consists of an encryption network for diffusing the image and a decryption network for restoring the plaintext image from the diffused image. To enhance the security of the encrypted image, the diffused image is further processed with two optional operations: parallel scrambling and serial diffusion. Two key planes are constructed based on a user-defined key with a chaotic map to control the authority to access images. The structure and parameters of FEDResNet can be shared publicly by different users; hence, it is more flexible and convenient than previous deep-learning-based image encryption methods. A classification network is trained to classify medical images in ciphertext environments. The proposed FEDResNet is trained and tested on the ImageNet data set. Extensive experiments have been performed, and the experimental results suggest that the proposed model can achieve a high level of security with satisfactory efficiency. The experimental results also show that FEDResNet-encrypted images can be classified directly in the ciphertext domain by authorized users as accurately as plaintext images, which is a superior property that is not possessed by traditional image encryption methods.

Color image compression and encryption scheme based on compressive sensing and double random encryption strategy

It is known that chaotic, especially hyperchaotic system can be suitable for the application in image encryption owing to itself characteristics. While currently, certain improved chaotic or hyperchaotic systems are confronted with the security issue of encryption due to their less complex dynamical behaviors. To address the problem well, we introduce a novel two-dimensional (2D) crossed hyperchaotic map which is based on the logistic map and the infinite collapse map. The analysis of phase diagram and Lyapunov exponential spectrum demonstrate that the given system can exhibit extensive hyperchaotic behavior and good traversal properties. Moreover, the growing use of digital images has prompted demand for multi-image encryption scheme. For this reason, based on the given 2D crossed hyperchaotic map, a multiple image encryption (MIE) scheme that employs a cross-plane with the operation of simultaneous permutation and diffusion to modify the values of its positions and pixels across multiple images is proposed. A pixel blur preprocessing technique is introduced such that the efficiency of key calculation and the speed and safety of information encryption are greatly improved. Eventually, some simulation examples and security analysis reveal that the put forward encryption scheme is able to keep out kinds of attacks such as the selective plaintext attacks and data loss.

This paper proposes a scheme of separable reversible information hiding (RIH) for encrypted images (EIs) in which hidden information can be extracted from an EI carrying information without image decryption. The proposed scheme firstly encrypts an image and simultaneously prepares room for RIH by two permutation ways. Information are, then, hidden into the EI by a RIH technique, and the EI carrying information is sent to a receiver. According to keys which the receiver has, he/she is allowed to take seven different actions, whereas the conventional scheme offers only three. This feature of the proposed scheme extends applicable scenarios. Moreover, the proposed scheme always recover the original image, whereas the conventional scheme sometimes fails to do.

A color image encryption and decryption scheme based on extended DNA coding and fractional-order 5D hyper-chaotic system

A novel image encryption scheme using both pixel level and bit level permutation with chaotic map

Recently, chaotic systems have been widely investigated in several engineering applications. This paper presents a new chaotic system based on Julia’s fractal process, chaotic attractors and Logistic map in a complex set. Complex dynamic characteristics were analyzed, such as equilibrium points, bifurcation, Lyapunov exponents and chaotic behavior of the proposed chaotic system. As we know, one positive Lyapunov exponent proved the chaotic state. Numerical simulation shows a plethora of complex dynamic behaviors, which coexist with an antagonist form mixed of bifurcation and attractor. Then, we introduce an algorithm for image encryption based on chaotic system. The algorithm consists of two main stages: confusion and diffusion. Experimental results have proved that the proposed maps used are more complicated and they have a key space sufficiently large. The proposed image encryption algorithm is compared to other recent image encryption schemes by using different security analysis factors including differential attacks analysis, statistical tests, key space analysis, information entropy test and running time. The results demonstrated that the proposed image encryption scheme has better results in the level of security and speed.

Chaotic maps used to shuffle and manipulate the image pixels are important for image encryption (IE). In this study, a novel 2D optimized chaotic map (OPMAP) using a triple-objective differential evolution (TODE) algorithm is presented for IE. A model for OPMAP with eight decision variables is empirically designed, and then its variables are determined utilizing TODE through minimizing a triple-objective function that involving Lyapunov exponent (LE), entropy and 0–1 test. OPMAP is assessed with respect to credible measurements like bifurcation, 3D phase space, LE, 0–1 test, permutation entropy (PE) and sample entropy (SE). The capability of OPMAP is then verified through an IE scheme including permutation and diffusion through various cryptanalyses: key space 2298, mean entropy 7.9995, mean correlation 13.61E-5, number of pixels changing rate (NPCR) 99.6093, unified average changing intensity (UACI) 33.4630 and encryption processing time (EPT) 0.2919 (s). A detailed review of IE schemes reported elsewhere is presented and IE performance of OPMAP is also validated by comparison with those IE schemes with and without optimization used. The 2D-OPMAP-based IE is faster and has low computational complexity. Moreover, the proposed it shows better cryptanalysis results for the most of the comparisons.

Trajectory control and image encryption using affine transformation of lorenz system

Joint image compression and encryption using a novel column-wise scanning and optimization algorithm