Secure Image Communication Research Articles

Integration of a novel 3D chaotic map with ELSS and novel cross-border pixel exchange strategy for secure image communication

This paper proposes a robust image encryption algorithm that utilizes a Novel three-dimensional (3D) Chaotic map and an Enhanced Logistic Sine System (ELSS). We leverage the unpredictability of 3D chaotic dynamics alongside the complexity of ELSS and DNA Sequence to forge a formidable image encryption scheme. Firstly, the image pixels are converted from decimal to hexadecimal notation and sorted in a 1D pixel array carrying a unique sequence of three channels of the RGB image. Secondly, the secret key is appended to XOR, the values with that 1-D pixels array. Thirdly, values are sorted by performing the binary right shift operation and encoded into DNA. Fourthly, a novel chaotic map is used to perform scrambling operations. Lastly, a novel enormous keyspace ELSS is used to perform efficient Border and Cross-Border (B &CB) pixel exchange, further enhancing the encryption quality of the proposed algorithm. Comprehensive security analysis proved that the proposed algorithm exhibits remarkable resilience against powerful known and chosen plaintext attacks and other prevalent cryptanalysis attacks, including differential attacks and exhaustive key search attacks. Henceforth, the proposed algorithm’s superior security and low computational cost make it an ideal choice for real-time secure image communication across various platforms, including satellite, multimedia, and military communications.

Secure image communication based on two-layer dynamic feedback encryption and DWT information hiding.

In response to the vulnerability of image encryption techniques to chosen plaintext attacks, this paper proposes a secure image communication scheme based on two-layer dynamic feedback encryption and discrete wavelet transform (DWT) information hiding. The proposed scheme employs a plaintext correlation and intermediate ciphertext feedback mechanism, and combines chaotic systems, bit-level permutation, bilateral diffusion, and dynamic confusion to ensure the security and confidentiality of transmitted images. Firstly, a dynamically chaotic encryption sequence associated with a secure plaintext hash value is generated and utilized for the first round of bit-level permutation, bilateral diffusion, and dynamic confusion, resulting in an intermediate ciphertext image. Similarly, the characteristic values of the intermediate ciphertext image are used to generate dynamically chaotic encryption sequences associated with them. These sequences are then employed for the second round of bit-level permutation, bilateral diffusion, and dynamic confusion to gain the final ciphertext image. The ciphertext image hidden by DWT also provides efficient encryption, higher level of security and robustness to attacks. This technology offers indiscernible secret data insertion, rendering it challenging for assailants to spot or extract concealed information. By combining the proposed dynamic closed-loop feedback secure image encryption scheme based on the 2D-SLMM chaotic system with DWT-based hiding, a comprehensive and robust image encryption approach can be achieved. According to the results of theoretical research and experimental simulation, our encryption scheme has dynamic encryption effect and reliable security performance. The scheme is highly sensitive to key and plaintext, and can effectively resist various common encryption attacks and maintain good robustness. Therefore, our proposed encryption algorithm is an ideal digital image privacy protection technology, which has a wide range of practical application prospects.

COLOR IMAGE ENCRYPTION THROUGH MULTI-S-BOX GENERATED BY HYPERCHAOTIC SYSTEM AND MIXTURE OF PIXEL BITS

The growing demand for maintaining secure communication channels with the advancements in digital technologies has led to an intensified interest in designing reliable image encryption schemes. Despite various encryption schemes that have been used, some are considered to have insecurity regarding data transmission and multimedia. Motivated by this concern, this paper proposes a new color image encryption algorithm of a multi-key generation-based nD-Hyperchaotic (HC) system. The new algorithm achieves Shannon’s confusion and diffusion principles using a two S-box generation approach, where the first S-box is generated from the proposed nD-HC system and the resulting sequence is used to increase encryption complexity, while the second S-box is generated from ([Formula: see text])D-HC system. Afterward, mathematical analysis is carried out to showcase the robustness and efficiency of the proposed algorithm, as well as its resistance to visual, statistical, differential, and brute-force attacks. The proposed scheme successfully passes all NIST SP 800 suite tests. The cryptographic system demonstrated by the proposed scheme has proven to have outstanding performance through simulation tests, which indicates promising potential applicability aspects in secure and real-time image communication settings.

An accelerated chaotic image secure communication system based on Zynq-7000 platform

An accelerated chaotic image secure communication system based on Zynq-7000 platform

Enhanced Semantic Visual Cryptography with AI-driven error reduction for improved two-dimensional image quality and security

Abstract Visual Cryptography (VC) has emerged as a vital technique in the information security domain, with the fundamental purpose of securing 2-Dimensional (2D) image content through encryption and facilitating secure communication. While traditional VC has been instrumental in safeguarding data, it often falls short in maintaining image quality and semantic accuracy upon reconstruction. To address these limitations, this research encompasses the development of an Enhanced Semantic VC (ESVC) model, which aims to refine the encryption process while ensuring the semantic integrity of the images. The ESVC model introduces a new approach that merges VC with artificial intelligence (AI) to enhance 2D image encryption and decryption. The novel aspect of this research lies in the integration of AI-driven reinforcement learning (RL) to increase the quality of the 2D image by measuring the errors between the original secret image and the reconstructed image. This innovative framework is tailored for the secure transmission of 2D grayscale images, ensuring the preservation of semantic integrity while measuring and minimizing image quality loss. By integrating RL algorithms with a measurement of error reduction protocol, the model promises robust encryption capabilities with enhanced resilience against a plethora of cyber threats, thereby elevating the standard for secure image communication. Empirical evaluation of the ESVC model yields promising results, with the Peak Signal-to-Noise Ratio (PSNR) of reconstructed images achieving impressive values between +39 and +42 decibels (dB). These findings underscore the ESVC model’s capability to produce high-fidelity decrypted images, significantly surpassing traditional VC methods in both security and image quality. The research findings illuminate the potential of merging AI with VC to achieve a harmonious balance between computational efficiency and encryption strength, marking a significant advancement in the domain of visual data protection.

Fuzzy adaptive event-triggered synchronization control mechanism for T–S fuzzy RDNNs under deception attacks

In this paper, a fuzzy-dependent adaptive event-triggered mechanism (FAETM) for synchronizing Takagi–Sugeno (T–S) fuzzy reaction–diffusion neural networks (RDNNs) is developed while considering deception attacks. Firstly, a general neural network model considering both fuzzy logic rules and reaction–diffusion terms is established. Secondly, a FAETM based on an aperiodic sampling period is presented under deception attacks to alleviate the communication burden, wherein the adaptive threshold function is dependent on membership functions. Moreover, a membership-function-dependent asymmetric Lyapunov functional (LF) is constructed, and some positive-definite and symmetric constraints of matrices are removed as a result. Based on the LF method and integral inequality techniques, the H∞ synchronization criteria for the T–S fuzzy RDNNs are presented by linear matrix inequalities (LMIs). Finally, one simulation example is exploited to demonstrate the feasibility and validity of the established method, and the outcome is applied to image secure communication.

Utilization of the double random phase encoding algorithm for secure image communication

Utilization of the double random phase encoding algorithm for secure image communication

Numerical analysis of a chaotic coupled hyperbolic PDE system for secure image encryption

This paper focuses on the interest of using chaotic hyperbolic Partial Differential Equations (PDE) systems synchronization for secure image communication. Such systems offer a promising alternative to finite dimensional chaotic systems with enlarged key space, efficient computation, and more complex dynamics. Here, we modify the classical chaotic hyperbolic PDE system by adding integral boundary couplings and potential terms. The chaotic behaviour of the resulting system is observed in numerical simulations. Adding such couplings allows to enhance the security of the cryptosystem. The synchronization of receiver and transmitter chaotic systems is achieved by the use of a chaotic observer designed using the backstepping methodology. The initial image can then be encrypted into a chaotic signal on the transmitter side before being sent to the receiver side. Using observational data, the receiver can then reconstruct the initial image. Numerical illustrations complete the paper.

Adaptive Event-Triggered Mechanism to Synchronization of Reaction–Diffusion CVNNs and Its Application in Image Secure Communication

This article is centered on the formulation of a refined adaptive sampled-data-based event-triggering control (ASDBETC) scheme for the synchronization of reaction–diffusion complex-valued neural networks (RDCVNNs) with probabilistic time-varying delays (TVDs). A refined ASDBETC mechanism is first proposed in a hierarchy structure, which differs from some conventional sampled-data-based event-triggering control mechanisms with preordained invariable threshold. The refined ASDBETC mechanism can adaptively adjust the orientation and frequency of event-triggered threshold parameters via the variational tendency of states and the corresponding Euclidean distance between states. Therefore, an intact bidirectional regulative mechanism that is sensitive to the changes of state is legitimately established to provide additional flexibility, which is conducive to better compromise between communication resources and control performance. Through considering the effect of uncertainties, the random TVDs belonging to two different intervals by a probabilistic form are introduced. Then, by leveraging a novel time-related Lyapunov–Krasovskii functional (LKF) that contains the more realistic sampled behaviors on the entire sampled interval, new synchronization conditions and controller design method are derived for RDCVNNs. Finally, the advantages of the refined ASDBETC strategy, the availability, and practicability of the developed theories are corroborated via two simulation examples.

Outlier-Resistant Nonfragile Control of T–S Fuzzy Neural Networks With Reaction–Diffusion Terms and Its Application in Image Secure Communication

This paper focuses on a new outlier-resistant non-fragile control issue for a class of Takagi-Sugeno (T-S) fuzzy delayed neural networks with reaction-diffusion terms (TFRDNNs). Compared with the existing delayed neural networks (DNNs), fuzzy control rules and reaction-diffusion phenomenon are considered simultaneously, which makes the proposed models more practical. Furthermore, when subjected to abnormal interference, measurement outputs result in measurement outliers. In order to mitigate the negative effects on estimation error, a state estimator scheme is presented by introducing a saturation function. By using an appropriate Lyapunov-Krasovskii functional (LKF) and with the help of a free weighting matrix, sufficient conditions can be deduced to guarantee the asymptotical stability and prescribed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {H}_{\infty }$</tex-math></inline-formula> performance index of the disturbance attenuation of estimation error. Next, a design strategy of outlier-resistant non-fragile state estimator (ONSE) is put forward by employing some decoupling techniques. An illustrative example is exploited to illustrate the validity and feasibility of the proposed state estimator. Finally, the obtained theoretical results are applied to image encryption. The experimental analysis demonstrates that the presented encryption scheme is feasible and effective.

Adaptive Event-Triggered Space-Time Sampled-Data Synchronization for Fuzzy Coupled RDNNs Under Hybrid Random Cyberattacks

This paper investigates the exponential synchronization of fuzzy coupling reaction-diffusion neural networks (RDNNs) under hybrid random cyber attacks. To efficaciously tolerate the cyber attacks and guarantee the expected performance for the proposed systems, a fuzzy-regulation-dependent adaptive spatiotemporal security sampled-data-based event-triggered control scheme (SDBETCS) is firstly introduced according to distinct fuzzy regulations. In light of the current and latest sampling signals, the threshold parameters can be timely and flexibly updated and the associated adaptive spatiotemporal SDBETCSs can be adaptively regulated for different fuzzy rules. In comparison with the conventional fuzzy SDBETCSs, the designed fuzzy adaptive spatiotemporal SDBETCS can not only reduce the event-triggering frequency but also effectively conserve more finite network communication resources. Through considering a discontinuous Lyapunov functional (LF), a new exponential synchronization criterion is provided for fuzzy coupling RDNNs. Furthermore, a more general fuzzy adaptive spatiotemporal SDBETCS with time-dependent and continuous threshold function is presented to compare with the traditional fuzzy SDBETCS. Lastly, demonstrative examples are given to verify the validity and feasibility of the theoretical analysis results and illustrate its potential application in image secure communication.

Secure Optical Image Communication Using Double Random Transformation and Memristive Chaos

The issue of information security in photonics environment has attracted more and more attention, especially when the secure communication of optical digital images has become a research hotspot. In this paper, we propose a hybrid encryption scheme for color images in the frequency and spatial domains based on double random transform and memristor hyperchaotic system. Firstly, we decompose the color image into RGB channels and then perform fast fourier transform (FFT) to transform the digital image from the spatial domain to the frequency domain. Secondly, two-phase masks are generated using the memristor hyperchaotic system, and the Fresnel diffraction optical transformation method is performed twice for encryption. Thirdly, the transformation from the frequency domain to the spatial domain is completed using inverse fast fourier transform (IFFT). Finally, the image is permuted and diffused using the chaotic sequences to obtain the final cipher image. Double random phase encryption expands the key space, while the combination of spatial and frequency domains improves the resistance to attacks. Based on cryptanalysis theory, we introduce a dynamic key associated with plain image, which can effectively resist plain attack. The experimental results show that the optical digital image encryption scheme has a large key space, excellent comprehensive performance, and can resist common attacks. In addition, we verify the hardware feasibility and ease of implementation of the proposed algorithm in an embedded optical communication network experimental platform. Therefore, our proposed scheme in this paper is a preferred optical digital image secure communication technology scheme with good application prospects.

A Color Image Encryption Algorithm Based on Hash Table, Hilbert Curve and Hyper-Chaotic Synchronization

Chaotic systems, especially hyper-chaotic systems are suitable for digital image encryption because of their complex properties such as pseudo randomness and extreme sensitivity. This paper proposes a new color image encryption algorithm based on a hyper-chaotic system constructed by a tri-valued memristor. The encryption process is based on the structure of permutation-diffusion, and the transmission of key information is realized through hyper-chaotic synchronization technology. In this design, the hash value of the plaintext image is used to generate the initial key the permutation sequence with the Hash table structure based on the hyper-chaotic sequence is used to implement pixel-level and bit-level permutation operations. Hilbert curves combining with the ciphertext feedback mechanism are applied to complete the diffusion operation. A series of experimental analyses have been applied to measure the novel algorithm, and the results show that the scheme has excellent encryption performance and can resist a variety of attacks. This method can be applied in secure image communication fields.

Exploiting compressed sensing and polynomial-based progressive secret image sharing for visually secure image selection encryption with authentication

Image encryption is an effective method to protect private images by converting them into meaningless ones, but many current image encryption algorithms still have security and efficiency problems. This paper combines compressed sensing (CS) and secret image sharing (SIS) to propose a certifiable visually secure image selection encryption. Firstly, a selective encryption based on multi-task convolutional neural network (SE-MTCNN) is presented to distinguish and encrypt the sensitive and non-sensitive information of plain images. Subsequently, the SIS algorithm is used to decompose the resulting plain image into multiple shadow images to disperse the risk of cryptographic image loss and resist hacking attacks. Herein, a pseudo-convolutional sliding scrambling based on chaotic sequences driven by plaintext (PCSS-CSDP) is proposed to eliminate the correlation between adjacent image pixels. Finally, the IWT-M-embedding algorithm is used to embed shadow images into carrier images to get multiple visually meaningful cipher images. Additionally, a new authentication scheme based on bit-level cyclic shifts and dynamic combination (AS-BCSDC) is introduced, and the obtained authentication information is fused into cipher images to prevent the deception of illegal users and malicious tampering of cloud platform. Experiments demonstrate the effectiveness of our algorithm, and it may be applied for image secure communication.

An Optical Image Encryption Algorithm Based on a Fractional-Order Laser Hyperchaotic System

In recent years, image encryption schemes based on optical methods have been extensively studied. However, possible optical encryption methods in combination with fractional-order laser hyperchaotic systems have not been reported. Therefore, an optical image encryption scheme based on fractional Fourier transform and five-dimensional host-induced nonlinearity fractional-order laser hyperchaotic system is studied in this paper. Firstly, the dynamical characteristics of the proposed fractional-order laser hyperchaotic system are analyzed, and the DSP platform is used to realize the system. Then, a novel image encryption scheme is proposed combining BP neural network, GF(17) domain diffusion and hyperchaotic, random point scrambling algorithm. Finally, the performance of the encryption scheme is analyzed in detail. This work provides an experimental basis and theoretical guidance for image secure communication combining fractional-order laser hyperchaotic systems and optical methods and offers a new research perspective for optical image encryption.

Improved reversible data hiding scheme employing dual image-based least significant bit matching for secure image communication using style transfer

Improved reversible data hiding scheme employing dual image-based least significant bit matching for secure image communication using style transfer

Memristive hyperchaos secure communication based on sliding mode control

In order to enhance the chaotic degree of cellular neural network (CNN), the memristive characteristic is combined in CNN, and a five-dimensional memristive CNN hyperchaotic system is designed. A secure communication system based on chaos synchronization is constructed by the full-dimensional state observer theory. The sliding mode control method is used to control chaos synchronization between the sending end and the receiving end and improve the robustness to the parameter uncertainties and disturbances in the system. An improved sliding mode surface is designed, and its convergence time is analyzed. Image secure communication, as an example, is given to verify the effectiveness of the proposed method. Image encryption is implemented by the hyperchaotic system, and image decryption is implemented by chaos synchronization based on the sliding mode control. Simulation experiment results show that the proposed sliding mode control method can be used to achieve the chaos synchronization of the hyperchaotic systems with parameter uncertainties and disturbances, and the proposed memristive hyperchaotic system can be applied to the secure communication based on the chaos synchronization.

Image encryption algorithm based on dynamic DNA coding operations and 3D chaotic systems

This paper presents a new image encryption algorithm based on 3D chaotic system and deoxyribonucleic acid (DNA) coding. It uses two keys, an external one of 128 bits long and an internal one of 64 gray values coming from the plain image. The initial conditions come from the two keys and vary from one line of the image to the other and from one image to the other and consequently the sequences of substitutions too. In general, in image encryption based on 3D chaotic systems, each chaotic variable is used independently of the others in one phase of the encryption. Here we use the zigzag process to combine the sequences from all the variables before using them simultaneously in the encryption process. DNA coding generally uses one of the 24 DNA rules and one of the 16 join operations to perform the encryption. Here we use all the 24 rules dynamically as well as the 16 join operations in the encryption. Also we apply the chaotic permutation on DNA chain. The logical DNA operations are used according to an algorithm similar to that of the Fast Walsh Transform (FWT) in those 24 DNA rules. The algorithm has been evaluated. It has good statistical properties of cipher images. The proposed system presents high sensitivity on the encryption-decryption keys and on the plain images. These latter features make the proposed algorithm very efficient, robust and resistant against brute force attacks and good for the future secure image communication.

Quantization synchronization of chaotic neural networks with time delay under event-triggered strategy.

This paper shows solicitude for the quantization synchronization of delayed chaotic master and slave neural networks under an dynamic event-triggered strategy. In virtue of a generalized Halanay-type inequality, a theoretical criterion for quasi-synchronization of master and slave neural networks is derived. Meanwhile, we can obtain an exact upper bound of synchronization error by using this criterion. Compared with output feedback controller with event triggering and quantization, the case where the controller only affected by quantization is also considered. Then, we exclude the Zeno behavior of the event-triggered controller. A sufficient criterion for the existence of the quantized output feedback controllers is also provided. A numerical example is cited to illustrate the efficiency of our theoretical criteria. In addition, some experiments of secure image communication are conducted under quasi-synchronization of master and slave neural networks.

Chaos-based image encryption strategy based on random number embedding and DNA-level self-adaptive permutation and diffusion

Some image encryption algorithms are difficult to resist the chosen-plaintext attack against special images, in order to solve this problem and improve the security of the algorithm, this paper proposes a novel image encryption scheme based on the chaotic system, random number embedding and DNA-level self-adaptive permutation and diffusion. The architecture of preprocessing, permutation and diffusion is adopted. Firstly, an image preprocessing based on random number embedding (IPRNE) is presented, specifically, embed random numbers into the plain image, and then perform partition XOR operation on random numbers and their surrounding pixels to preprocess plain image. The random numbers are generated by a 4D memristive hyperchaotic system, and their embedding positions are controlled by the pixel sums of plain images. Secondly, the obtained image is encoded into a DNA matrix by use of a DNA encoding rule, and then a DNA-level self-adaptive permutation and diffusion processes are successively performed on it. Further, after decoding the diffused matrix, the cipher image is obtained. Besides, the feature information of DNA sequences of plain image is applied for disturbing the permutation and diffusion phases, which may be extracted automatically in the decryption process, and thus additional transmission and storage are avoided. Moreover, the plain image information and hyperchaotic system are integrated to design the DNA encoding /decoding rule for the plain image and mask matrix, and this can enhance the ability of the algorithm to resist chosen-plaintext attack. Experimental results and security analyses demonstrate that the proposed encryption is secure and effective, and it can be applied for image secure communication.