Arnold Transformation Research Articles

A secure and effective image encryption scheme by combining parallel compressed sensing with secret sharing scheme

In the complex network environment, it is becoming more and more significant to protect the security of information during transmission. A secure and effective image encryption scheme by combining parallel compressed sensing with secret sharing scheme is presented in this paper. Firstly, an image is measured by parallel compressed sensing, which not only realizes compression and encryption in the meantime, but also reduces computational complexity and storage space, and enhances transmission efficiency. Secondly, a block Arnold transformation is applied to process the measurement value image, and the obtained image is called a secret image, so as to achieve the effects of scrambling and encryption. Then, the secret image is partitioned into n shadow images by Shamir’s (t,n)-threshold secret sharing scheme, at least any t of n shadows images are able to recover the secret image, so the size of shadow images can be adjusted according to different application scenarios, which is flexible. This method realizes the encryption effect, and enhances the security of the secret image. Finally, to ensure the security of shadow images, the Zigzag confusion is introduced to process n shadow images and realizes the encryption effect. Experimental results manifest that our scheme realizes security and availability of the network system under the condition of limited resources.

Image Encryption Algorithm Based on Arnold Transform and Chaos Theory in the Multi-wavelet Domain

Image encryption is essential for ensuring data transmission security over open public networks. Using Multi-Wavelet Transform, Arnold transform, and two chaotic systems, a novel color image encryption technology is designed in this paper. In the proposed algorithm, the primary color components of the input image undergo a multi-wave transform before the Arnold Transform confounds the sub-bands of each color component. Each color component is then divided into blocks shuffled in a predetermined order. Finally, the encrypted image is generated using secret keys derived from Nahrain’s and WAM’s chaotic systems. Notably, the initial conditions of the chaotic maps are generated using image data to increase the algorithm’s sensitivity to the input image. Security analyses conducted to validate the practicability of the new algorithm reveal that it possesses excellent encryption efficiency, high key sensitivity, and the ability to withstand a wide variety of attacks.

Image encryption algorithm based on 2D‐CLICM chaotic system

AbstractImage encryption algorithm based on a two‐dimensional Chebyshev‐Logistic‐Infinite Collapse Map (2D‐CLICM) is proposed. A new two‐dimensional chaotic map is designed, and numerical studies show that 2D‐CLICM has a larger chaotic region, better randomness and more complex chaotic behavior. An image encryption algorithm (CLICM‐IE) is developed based on the 2D‐CLICM. The randomly generated key is used to generate more random chaotic sequences and the security is greatly improved. To obtain lower computation and time complexity, the whole process performs row encryption for each image pixel. The Arnold transformation preprocesses the image and then the encryption of image pixels is accomplished by controlling the random confusion and diffusion parts with the sequence generated by 2D‐CLICM. The results show that the CLICM‐IE algorithm is deeply random and unpredictable, and resists a variety of attacks. These results can provide good basis and practical application for the chaos generation and image encryption.

Development of a cropping resilient watermarking scheme based on contourlet transform for secure IoT communication

The objective of this work is to propose a robust watermarking method as watermarking techniques are widely used today for preventing image altering and duplication. With the growth of image-based IoT applications nowadays, the need for developing robust digital watermarking techniques is of high demand. In this work, a robust yet highly perceptible watermarking scheme is proposed. The proposed scheme is based on the Contourlet Transform (CT) and Singular Value Decomposition (SVD) as the embedding domain in which the high-frequency components are chosen for embedding. The frequency domain is selected in order to make the watermarking scheme resists image attacks as the watermark is spreaded across different frequency bands in the cover image and hence the possibility of altering all the embedded bands is not possible as it will results in destroying the cover image. On the other hand, the Arnold transformation was used to insure secure IOT communication where the Arnold transform is applied to the binary logo watermark before embedding for a more secure design. In this context, the host image has been decomposed into the first level of contourlet transform and the highest frequency sub-bands are selected for embedding after performing the SVD on those bands where the SVD matrix is chosen to be the embedding domain. Moreover, This work aims to resist the cropping attack on images where PSNR values were above 52 dB and NC values ranged from 0.8 to 0.9 under various types of cropping attacks. In addition, the proposed method demonstrates its ability to resist various geometric and noise attacks such as JPEG compression, histogram equalization, gaussian noising and image brightening. Comparisons with state-of-the-art work demonstrate the proposed scheme's efficienc

Quantum Color Image Encryption Scheme Based on 3D Non-Equilateral Arnold Transform and 3D Logistic Chaotic Map

Quantum Color Image Encryption Scheme Based on 3D Non-Equilateral Arnold Transform and 3D Logistic Chaotic Map

An Optimized Image Encryption Scheme, Leveraging the Arnold Transform and Chaotic Map

An Optimized Image Encryption Scheme, Leveraging the Arnold Transform and Chaotic Map

Efficient Scrambling-Substitution Image Security Scheme using Chaotic Arnold-Logistic Maps in the Discrete Cosine Transform

This paper introduces an efficient scrambling-substitution image security scheme using chaotic Arnold and Logistic (Arnold-Logistic) maps in the discrete cosine transform (DCT). The Arnold map is employed as a scrambling stage while the Logistic map is employed as a substitution stage. The hybrid Arnold-Logistic mapping is performed in the DCT. The encipherment phase of the introduced DCT-based Arnold-Logistic security scheme begins by applying the DCT to the plainimage and the resulted DCT coefficient of the plainimage are scrambled for m iterations using the Arnold transformation. Then, the Arnold-based transformed DCT coefficients are substituted for n iterations using the Logistic map and the inverse of DCT (IDCT) is employed to produce the cipherimage. The decipherment phase of the introduced DCTbased Arnold-Logistic security scheme is the inverse of the encryption stage and begins by applying the DCT to the cipherimage. The resulted DCT coefficient of the cipherimage is inversely substituted for n iterations using the inverse Logistic map. Then, the inverse Logistic-based transformed DCT coefficients are inversely scrambled for m iterations using the inverse Arnold map and the IDCT is employed to produce the decrypted image. A series of test experiments are applied to investigate the introduced DCTbased Arnold-Logistic security scheme. The outcome results demonstrated the superiority of the introduced DCT-based Arnold-Logistic security scheme from the security point of view.

Digital Watermarking-Based Cryptosystem for Cloud Resource Provisioning

Cloud computing resource privacy is important and it becomes stronger when image-based security is applied. Most cloud service providers provision resources for images to the end users. Numerous encryption strategies are applied to safeguard information of the image while empowering visual component extractions. The work uses wavelet domain technique, visual cryptography, and Arnold transformation. This scheme provides additional security features to the secret share image at the trusted authority side for copyright protection of digital images. The proposed technique is robust against some selected attacks like scaling, blurring, etc. This technique protects the copyright of digital data over the cloud. It is a need and necessary to protect and prevent the illegal copying, redistribution, and copyright infringement of multimedia. This research work aims at increasing robustness and security of the digital image copyright scheme. The proposed scheme is a hybrid authentication framework that will perform better in the watermarking system of security using simulation over MATLAB.

Robust Watermarking Method for Secure Transmission of Medical Images in EHR Systems

Confidentiality of Electronic Health Record (EHR) and privacy are two important security requirements for healthcare systems. Many devices on the EHR network utilize little or no encryption, which makes data in transit vulnerable to exploitative attacks, such as Man-in-the-Middle and other filtration methods. Recently, watermarking algorithms as an efficient response to these requirements is in the underline. In this paper, we present a robust watermarking method conceived as part of an Electronic Health Record platform. In this method a chaotic encryption and blind medical image watermarking technique was incorporated into the system as an authorization mechanism to ensure confidentiality and integrity of electronic health information. We present a hybrid watermarking method based on a combination of discrete wavelet transform (DWT), hessenberg Decomposition (HD), Singular value decomposition (SVD) and an original chaos crypto system based on the Arnold Transform (AT) of Singular Value Decomposition. In order to spread the robustness of our algorithm and provide additional security, an improved SVD-AT embedding and extraction procedure has been used to scramble the EHR data in the preprocessing step of the proposed method. In the process of watermark embedding, an R-level discrete wavelet transform was applied to the host image. The low frequency wavelet coefficients are selected to carry this scrambled-watermark. In extraction process, the stored used plain image is obtained from the trusted authority server to complete the verification process. The receiver should compare the unsigned watermark with the extracted watermark again. The verification can be done before clinical procedures and diagnosis. The proposed watermarking method endures entirety attacks and rightly extracts the hidden watermark without significant degradation in the image quality, thus, when the Peak Signal to Noise Ratio (PSNR) and Normalized Correlation (NC) performance of the proposed algorithm is performed.

An efficient CNN based epileptic seizures detection framework using encrypted EEG signals for secure telemedicine applications

Recently, the rapid development of Artificial Intelligence (AI) applied in the Medical Internet of Things (MIoT) for the diagnosis of diseases such as epilepsy based on the investigation of electroencephalography (EEG) signals. Thanks to AI-based deep learning models, the procedure of epileptic seizure detection can be performed professionally in Smart Healthcare. However, the security issues for protecting sensitive medical EEG signals from disclosure and unauthorized operations from severe attacks over open networks. Therefore, there is a serious need for providing an effective method for encrypted EEG classification and prediction. In this paper, a new and efficient encrypted EEG data classification and recognition system using Chaotic Baker Map and Arnold Transform algorithms with Convolutional Neural Networks (CNNs). In this system, the channel's EEG time series is first converted into a 2D spectrogram image and then encrypted using Chaotic Baker Map and Arnold Transform algorithms, and finally fed to CNNs-based Transfer Learning (TL) models. From the experimental results, the proposed approach is validated and evaluated on a public CHB-MIT dataset and the googlenet with encrypted EEG images provides satisfactory performance by outperforming the models of other CNN like Alexnet, Resnet50, and squeezenet.

A Novel Image Encryption Algorithm Based on Improved Arnold Transform and Chaotic Pulse-Coupled Neural Network.

Information security has become a focal topic in the information and digital age. How to realize secure transmission and the secure storage of image data is a major research focus of information security. Aiming at this hot topic, in order to improve the security of image data transmission, this paper proposes an image encryption algorithm based on improved Arnold transform and a chaotic pulse-coupled neural network. Firstly, the oscillatory reset voltage is introduced into the uncoupled impulse neural network, which makes the uncoupled impulse neural network exhibit chaotic characteristics. The chaotic sequence is generated by multiple iterations of the chaotic pulse-coupled neural network, and then the image is pre-encrypted by XOR operation with the generated chaotic sequence. Secondly, using the improved Arnold transform, the pre-encrypted image is scrambled to further improve the scrambling degree and encryption effect of the pre-encrypted image so as to obtain the final ciphertext image. Finally, the security analysis and experimental simulation of the encrypted image are carried out. The results of quantitative evaluation show that the proposed algorithm has a better encryption effect than the partial encryption algorithm. The algorithm is highly sensitive to keys and plaintexts, has a large key space, and can effectively resist differential attacks and attacks such as noise and clipping.

A Novel Virtual Optical Image Encryption Scheme Created by Combining Chaotic S-Box with Double Random Phase Encoding.

The double random phase encoding (DRPE) system plays a significant role in encrypted systems. However, it is a linear system that leads to security holes in encrypted systems. To tackle this issue, this paper proposes a novel optical image encryption scheme that combines a chaotic S-box, DRPE, and an improved Arnold transformation (IAT). In particular, the encryption scheme designs a chaotic S-box to substitute an image. The chaotic S-box has the characteristics of high nonlinearity and low differential uniformity and is then introduced to enhance the security of the DRPE system. Chaotic S-boxes are resistant to algebraic attacks. An IAT is used to scramble an image encoded by the DRPE system. Meanwhile, three chaotic sequences are obtained by a nonlinear chaotic map in the proposed encryption scheme. One of them is used for XOR operation, and the other two chaotic sequences are explored to generate two random masks in the DRPE system. Simulation results and performance analysis show that the proposed encryption scheme is efficient and secure.

Unmodulated fully-phase and shifted-phase encoded encryption key using Arnold transform and joint fractional Fourier transform correlator

We propose a nonlinear image encryption system using Arnold transform (ART) and a fully-phase encoded images as inputs to a nonzero-order joint transform correlator (JTC) in the fractional Fourier transform (FRFT) domain. Unlike other reported works, the fully-phase image along with two random-phase masks (RPMs) are introduced directly without linear phase modulation at the input plane of the JTC where the FRFT modulates this joint input image and produces the joint fractional power distribution (JFPD) at the output plane. It will be demonstrated that using modulating inputs in the optical setup makes the decryption scheme prone to error and leads to retrieving image failure. Further, a shifted-phase encoded key mask is applied in this proposal to achieve the non-zero order JFPD, which is adjusted by a nonlinear operation to guarantee a securely and high-quality retrieved ciphertext image. Furthermore, the proposed encryption scheme has four security keys: (i) two-random-phase masks, (ii) an ART frequency parameter, and (iii) a fractional order of the FRFT. It will be demonstrated that the decryption process is very sensitive to small variations of the ART frequency parameter, the fractional order of the FRFT, and the RPM. The cryptanalysis shows that the proposed encryption system is very invulnerable to Chosen plaintext (CPA), known plaintext (KPA), ciphertext only (COA) and brute force attacks. In addition, the robustness of the proposed scheme against noise and occlusion is presented using computer simulations.

A hyperchaotic image encryption scheme based on the triple dislocation of the Liu and Lorenz system

This paper proposes a novel color image encryption scheme of Liu Lorenz-XOR Zigzag Arnold (LL-XZA) encryption algorithm. Firstly, to prove that the three-dimensional(3D) Liu system and the four-dimensional(4D) Lorenz system are in a hyperchaotic state, we performed the visual analysis of their key parameters, such as the Lyapunov exponent, bifurcation diagram, attractor, Poincare cross-section diagram and initial value sensitivity. Then, we adopt the 3D Liu hyperchaotic system as the primary hyperchaotic mapping scheme of the color image. The 4D Lorenz hyperchaotic system is discretized by the Runge–Kutta method to generate a pseudorandom number sequence of the control parameter with stronger randomicity. Furthermore, XOR, 3D Zigzag transformation, and 3D Arnold transformation are reset to construct the encryption scheme. Finally, we explored the security performance of the proposed scheme with the RGB grayscale histogram, pixel correlation, information entropy by color image simulation. The results verified that the LL-XZA encryption algorithm can significantly improve the color image security performance and has superiorities in stable encryption effect, visual security, and robustness.

Arnold Transform Based Medical Image Scrambling and Reconstruction Technique with Improved PSNR Parameter for Increasing the Robustness of Digital Watermarking Algorithms in Comparison with Random Shuffling Method

In this work, a new transform-based technique to secure the data in watermarking algorithm is proposed. Materials and methods: In this research, Arnold transform-based image scrambling method developed and compared with random shuffling method and 30 is the sample size of each group. All medical images are collected from standard medical database. Results: The execution of image scrambling algorithm is calculated using peak signal to noise ratio (PSNR) and universal index quality measure (UIQI) parameters. Low values of PSNR and UIQI represent higher scrambling. Arnold transform provides mean PSNR value of 7.1314db and UIQI is 69.0437%. Random shuffling provides mean PSNR value is 9.2890db, and UIQI is 75.3633%. Conclusion: Based on the experimental and the statistical analysis by using the independent sample T test, the Arnold transform-based image scrambling method performs significantly better than random shuffling method with PSNR (P=0.01) and UIQI (P=0.21).

A novel zero-watermarking scheme based on NSCT-SVD and blockchain for video copyright

With the advent of information era, the issues on video copyright continue to emerge. In the grey industrial chain of piracy, the film industry is suffering a major disaster area. The current protection schemes for video copyright are inefficient and costly so that video industry still has to face the infringement. To address poor robustness, weak imperceptibility and difficulty in traceability of the current protection schemes for video copyright, this paper proposes a novel zero-watermarking scheme based on NSCT-SVD and blockchain for video copyright. In addition, we research the feasibility and reason of combining zero-watermarking with blockchain. The designed zero-watermarking algorithm is based on NSCT-SVD, Arnold Transform and key-frames extraction algorithm which is based on distance threshold clustering. The results show the extracted features from video are stable and secure than DWT-SVD based and the past non-blocking. The performance of the blockchain scheme designed for video copyright practices well. Comparatively, the discussion and results showed that the proposed scheme has been verified more credible and efficient in authoritative traceability compared to trusted third party based. The registration information cannot be tampered and be more suitable for copyright protection.

A Fast Image Encryption Algorithm Based on Improved 6-D Hyper-Chaotic System

Aiming at the security and efficiency of image transmission, a fast image encryption algorithm based on an improved 6-D chaotic system is proposed. Firstly, we design a hyper-chaotic system with more complex chaotic behavior, analyze the Lyapunov exponential spectrum, chaotic attractor and randomness of the system, and generate random sequences through randomness enhancement operation. Secondly, image preprocessing is used to select pixels from the original image to form a thumbnail, the size of the key space can be changed by adjusting the thumbnail. Thirdly, the hash value of the original image is used as the initial values of the hyper-chaotic system to realize the uniqueness of the key. The row encryption matrix and column encryption matrix are generated according to the maximum and minimum values of row and column pixels in the thumbnail. These two encryption matrices are composed of the full arrangement of random sequences, which refers to the random combination of random sequences in a certain order. Before the encryption, the Arnold transformation is performed on the original image and then the cipher image is obtained by row encryption and column encryption respectively. The experimental results illustrate that the proposed algorithm has excellent security performance, robustness and the speed of encryption and decryption is very fast.

A Novel Video Copyright Protection Scheme Based on Blockchain and Double Watermarking

With the continuous development of multimedia, more and more digital works such as videos are spread, stored, and used in the network. In recent years, digital copyright infringement disputes have occurred frequently. The traditional copyright protection system has some problems, such as difficulty confirming copyright, monitoring infringement, and obtaining evidence for rights protection. To this end, we have designed and implemented a novel video copyright protection scheme based on the blockchain and double watermarking technology. We use the image correlation coefficient method to extract video keyframes. And we combine with Contourlet Transform domain, QR decomposition, and SIFT algorithm to improve the robustness of watermark against geometric attacks on the premise of invisibility. After that, we use Arnold Transformation (Cat Map) based on the Maximum Entropy Threshold Segmentation to encrypt the robust watermark and strengthen the security. Moreover, based on the characteristics of the fragile watermarking, we accurately locate the attacked video’s tamper position and complete the integrity authentication of the watermarked video. In addition, the hash digest of the video watermark and the user ID of the copyright owner is signed by SM2 and uploaded to the blockchain. The user can register the copyright after passing the identity authentication. We conduct tests and security analysis on the blockchain performance of the system, the performance of the commercial cryptography algorithm, and the security of the watermarking system. The experimental results show that the blockchain used in this system conforms to the industry standard, the performance of SM2 and SM3 is better than ECC-256 and SHA-256, and the system security is well guaranteed.

A new color image encryption technique using DNA computing and Chaos-based substitution box

In many cases, images contain sensitive information and patterns that require secure processing to avoid risk. It can be accessed by unauthorized users who can illegally exploit them to threaten the safety of people’s life and property. Protecting the privacies of the images has quickly become one of the biggest obstacles that prevent further exploration of image data. In this paper, we propose a novel privacy-preserving scheme to protect sensitive information within images. The proposed approach combines deoxyribonucleic acid (DNA) sequencing code, Arnold transformation (AT), and a chaotic dynamical system to construct an initial S-box. Various tests have been conducted to validate the randomness of this newly constructed S-box. These tests include National Institute of Standards and Technology (NIST) analysis, histogram analysis (HA), nonlinearity analysis (NL), strict avalanche criterion (SAC), bit independence criterion (BIC), bit independence criterion strict avalanche criterion (BIC-SAC), bit independence criterion nonlinearity (BIC-NL), equiprobable input/output XOR distribution, and linear approximation probability (LP). The proposed scheme possesses higher security wit NL = 103.75, SAC ≈ 0.5 and LP = 0.1560. Other tests such as BIC-SAC and BIC-NL calculated values are 0.4960 and 112.35, respectively. The results show that the proposed scheme has a strong ability to resist many attacks. Furthermore, the achieved results are compared to existing state-of-the-art methods. The comparison results further demonstrate the effectiveness of the proposed algorithm.

Enhanced image security using residue number system and new Arnold transform

This paper aims to improve the image scrambling and encryption effect in traditional two-dimensional discrete Arnold transform by introducing a new Residue number system (RNS) with three moduli and the New Arnold Transform. The study focuses on improving the classical discrete Arnold transform with quasi-affine properties, applying image scrambling and encryption research. The design of the method is explicit to three moduli set {2n, 2n+1+1, 2n+1-1}. These moduli set includes equalized and shapely moduli leading to the effective execution of the residue to binary converter. The study employs an arithmetic residue to the binary converter and an improved Arnold transformation algorithm. The encryption process uses MATLAB to accept a digital image input and subsequently convert the image into an RNS representation. The images are connected as a group. The resulting encrypted image uses the Arnold transformation algorithm. The encrypted image is used as input at decryption using the anti-Arnold (Reverse Arnold) transformation algorithm to convert the picture to the original RNS (original pixel value). Then the RNS was used to retransform the original RNS to its binary form. Security analysis tests, like histogram analysis, keyspace, key sensitivity, and correlation coefficient analysis, were administered on the encrypted image. Results show that the hybrid system can use the improved Arnold transform algorithm with better security and no constraint on image width and size.