Number Of Pixel Change Rate Research Articles

Protecting Sensitive Images with Improved 6-D Logistic Chaotic Image Steganography

In the digital age, strong methods for safeguarding sensitive data are essential. Image steganography is a practical technique for data protection that hides information inside seemingly authentic images. The proposed method increases security by using chaotic based image encryption and decryption. Encryption approaches based on chaotic logistic theory present an abundance of attractive and novel opportunities for developing secure image encryption methods. Nevertheless, these maps are frequently used for specific, unpredictable starting parameters. This problem is addressed by the research's Tabu search optimisation method. This method optimises chaotic map initial settings using a fitness function with numerous objectives. For image encryption, the most efficient methods are used to produce confidential keys. The input picture undergoes horizontal and vertical diffusion and permutation during encryption. These operations further scramble the image data, making it even more difficult to detect the hidden information. The primary goal is to develop a safe method for encrypting both color and grayscale images. Two common grayscale and color images that are accessible to the public were used to test the suggested strategy. compare our method with key existing works, specifically on the basis of Number of Pixels Change Rate (NPCR), Unified Average Changing Intensity (UACI), Peak Signal-to-Noise Ratio (PSNR) and speed, respectively, our approach improves upon these studies. Our results demonstrate that 7.9981, 99.8245, 35.6507, and 78.871 are the greatest values of entropy, NPCR, UACI, and PSNR, respectively. Whereas the respective speeds of encryption and decryption increase to 0.8433 and 1.4387 seconds. This innovative approach presents a powerful tool for applications requiring secure image steganography

6D Hyperchaotic Encryption Model for Ensuring Security to 3D Printed Models and Medical Images

In the 6G era, where ultra-fast and reliable communication is expected to be ubiquitous, encryption shall continue to play a crucial role in ensuring the security and privacy of data. Encryption and decryption of medical images and 3D printed models using 6D hyperchaotic function is proposed in this research work for ensuring security in data transfer. Here we envisage using a six-dimensional hyperchaotic system for encryption purposes which shall offer a high level of security due to its complex and unpredictable dynamics with multiple positive Lyapunov exponents. This system can potentially enhance the encryption process for 3D objects and medical images, ensuring the protection of sensitive data and preventing unauthorized access. A hyperchaotic system is a type of dynamical system characterized by exhibiting more than one positive Lyapunov exponent, which indicates strong sensitivity to initial conditions. These systems have more degrees of freedom and complex and intricate dynamics compared to standard chaotic systems. The security of the encryption scheme depends on the complexity of the hyperchaotic system and the randomness of the secret key. The parameters of a 6D hyperchaotic system shall be used as an encryption key with six dimensions, each with its range of values, and shall provide many possible keys. In this work, we implemented a 6D hyperchaotic system for the encryption of the 3D printed model and medical images. The performance evaluation was done by metrics entropy, correlation, Number of Pixels Change Rate (NPCR), and Unified Averaged Changed Intensity (UACI) which revealed the robustness of the encryption model in ensuring security. Hyperchaotic systems can be efficiently implemented in parallel computing architectures, which allow faster encryption and decryption processes.

Efficient Image Encryption via 2D Logistic Chaos Mapping: Strengthening Security with Pixel-Level Dynamics

This study presents an innovative image encryption algorithm anchored on the two-dimensional Logistic chaotic system, designed to address the limitations of traditional methods in terms of speed and security. The algorithm employs pixel shifting and scrambling, coupled with a segmented grayscale value substitution, to achieve a high level of security with strong key sensitivity and robust resistance to both differential and statistical attacks. Experimental validation demonstrates its superiority with fast encryption speeds, as evidenced by an encryption time of 0.2136 seconds for a 256×256 color image, and an entropy close to its ideal value, indicating excellent randomness. This method also exhibits high performance in resisting differential attacks, with Number of Pixels Change Rate (NPCR) and the Unified Average Changing Intensity (UACI) values nearing their optimal expected values. The integration of Quantum Key Distribution (QKD) is suggested for future work to enhance security against quantum computing threats, solidifying the algorithm’s potential as a leading solution for the image encryption.

Chaos and DNA coding technique for image cryptography

AbstractIn today's cybersphere, cryptography plays a vital role in various fields. Image encryption is an integral part for securing information because of its vast application areas such as military (defense), multimedia, healthcare and so forth. In this article, an image encryption algorithm for both grayscale and color image is proposed based on Tangential Delay‐Ellipse Reflecting Curve System (TD‐ERCS) chaotic map system and deoxyribonucleic acid (DNA) coding. Chaotic map is used to scramble the pixel positions; to achieve confusion and for creation of mask image, and DNA coding is used for changing the pixel values; to achieve diffusion. Upon experimental analysis, proposed work achieved significantly high mean square error and low peak signal to noise ratio, almost zero correlation, high number of pixel change rate and unified averaged changed intensity values, and resistance to noise and data loss attacks. In addition, the decryption is possible without loss in quality of image.

A quantum image encryption method for dual chaotic systems based on quantum logistic mapping

On the basis of using quantum NEQR (novel enhanced quantum representation of digital image) to display images, a dual chaos system based on quantum logistic mapping is proposed to encrypt quantum images to ensure the security of quantum image transmission. The encryption algorithm is based on quantum logistic mapping and Chen chaos system to generate chaotic sequences, and uses quantum rotation gate operations to rotate and transform each pixel of the quantum image to achieve the effect of image encryption. Traditional quantum image encryption usually uses classical randomly generated sequences to construct the encryption angle of the quantum rotating door. This method combines the randomness of measured quantum with the chaotic system to obtain a truly random sequence. Using this random sequence can better Keep images confidential. Experimental results show that this method has high security and sensitivity to keys. In the sensitivity analysis of the results of the simulation experiment, its NPCR (Number of Pixels Change Rate) values floated around 99.60%. In the field of image encryption, the reliability of image encryption is greatly enhanced.

An Enhanced Security in Medical Image Encryption Using Dynamic Chaotic Fuzzy Based Technique

As IoT and cloud computing have grown in popularity, medical images are now often transmitted between devices or accessed directly from the cloud. With this, the security is always a concern as these images are prone to many types of attack. We have proposed a proven method that is efficient in terms of security, time complexity, and integrity in order to be cloud-friendly so that it may be launched into the cloud and made accessible to users at any time. The goal of the work is to create a dynamic key that, depending on fuzzy values, alters the reproduction rate parameters with each repetition. By applying the last chaotic value created from the previous iteration, the fuzzy triangular membership function has been used in this manner to generate the reproduction rate parameter. The uniqueness and major benefit of the suggested strategy are that it can increase the security of the algorithm that makes use of a chaotic map and a static key. The method has been put forth when designing algorithms so that it should not only demonstrate security against different attacks but also provide efficiency towards computational complexity. The technique has been tested against a set of images and an existing algorithm using a variety of security metrics, including the correlation coefficient, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), and entropy. It has been determined from the comparative analysis that the proposed approach can make the existing algorithm more secure.

A new method of image encryption using advanced encryption Standard (AES) for network security

With the rapid increase in the use of technology, images have become a major source of sharing personal, confidential and official information and there is a dire need to protect this secret data. Image encryption plays major role in the security of images and there are many techniques developed for this purpose. Chaos based image encryption has now become most applicable and beneficial technique for image encryption. The purpose of this paper is to highlight a new method of image encryption with the use of advanced encryption standard (AES) and chaotic maps. This technique is composed of substitution and permutation phases. AES is found to be most secure cipher until now against different kinds of attacks. The round keys are generated by AES using key expansion algorithm. The sensitivity of this technique is that it is dependent on initial values and input image. S-boxes in AES introduce non-linearity, confusion, and an avalanche effect, enhancing security and resistance to cryptographic attacks by substituting bytes in the encryption process. The combination of AES and chaotic maps in encryption schemes provides a two-tiered approach to enhance security. AES offers a strong and well-established encryption method, while chaotic maps introduce randomness and complexity, making it more difficult for attackers to decipher encrypted data. This combination is often used to achieve a higher level of encryption security in various applications, including data transmission and storage. Different kinds of analysis and tests are performed on the technique which includes information entropy, number of pixel change rate (NPCR), and peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI) and histogram correlation of adjacent pixels. The results of these tests show that this technique is secure and resistant towards attacks.

A Comparative Assessment of Homomorphic Encryption Algorithms Applied to Biometric Information

This paper provides preliminary research regarding the implementation and evaluation of a hybrid mechanism of authentication based on fingerprint recognition interconnected with RFID technology, using Arduino modules, that can be deployed in different scenarios, including secret classified networks. To improve security, increase efficiency, and enhance convenience in the process of authentication, we perform a comparative assessment between two homomorphic encryption algorithms, the Paillier partial homomorphic algorithm and the Brakerski–Gentry–Vaikuntanathan fully homomorphic encryption scheme, applied to biometric templates extracted from the device mentioned above, by analyzing factors such as a histogram analysis, mean squared error (MSE), peak signal-to-noise ratio (PSNR), the structural similarity index measure (SSIM), the number of pixel change rate (NPCR), the unified average changing intensity (UACI), the correlation coefficient, and average encryption time and dimension. From security and privacy perspectives, the present findings suggest that the designed mechanism represents a reliable and low-cost authentication alternative that can facilitate secure access to computer systems and networks and minimize the risk of unauthorized access.

Hybrid Chaotic-Based PRNG for Secure Cryptography Applications

This paper suggests a novel one-dimensional (1D) map to address the limitations of traditional chaotic 1D maps. In contrast to traditional 1D maps, the proposed map has three control parameters a, μ, and c, allowing it to exhibit chaotic behavior over a wide range of values. The dynamic behavior of the new 1D map was analyzed using well-known numerical methods, including the bifurcation diagram and Lyapunov exponent. Both tests showed their complex and diverse behavior. In addition, a novel image encryption scheme was devised using the new function as its pseudorandom number generator. Rigorous statistical testing was applied to the proposed encryption algorithm. The mean square error (MSE) and peak signal-to-noise ratio (PSNR) results, in addition to subjecting 28 images to number of pixels change rate (NPCR) and unified average changing intensity (UACI) tests demonstrated the robustness of the system. The results of this study demonstrate the effectiveness of the new 1D map for use in secure image cryptography applications, providing a more robust and secure alternative to traditional chaotic 1D maps.

Development of playfair cryptosystem based on generation a multi-dimensional key matrix

Playfair is considered as one of the classical encryption symmetric methods, it has a limitation of using just 5×5 matrix, which means only 25 English letters could be represented. In this work, a 2D and 3D method is adopted as an expanded matrix that encompass the overall American standard code for information interchange (ASCII) codes in a permuted manner for all symbols of any language. Any sort of the multi-dimensional matrix will enhance the security by increasing the complexity on the attacker to try 256! patterns of keys probabilities instead of 25!. The key-matrix is generated from the chaotic maps for some control parameters as patterns of non-repeating random numbers from 0 to 255 equivalent to their ASCII code values. The security of the proposed method not rely only on the number of key probabilities, but exceed that to: matrix dimensionality, encryption/decryption algorithms, initial chaotic parameters, and key-matrix values permutation. The efficiency of the proposed cryptosystem has been investigated when tested on 784 samples according to security measurements in which the obtained number of pixels change rate (NPCR) (99.609) is very close to the ideal value, while the correlation plotting close to zero (0.00058) and entropy near from 8 (7.9998).

PSEUDO RANDOM KEY GENERATOR USING FRACTAL BASED TRELLIS CODED GENETIC ALGORITHM FOR IMAGE ENCRYPTION

Cryptographic applications such as online banking, and securing medical and military data require the usage of random keys, which should remain unpredictable by adversaries. This paper focuses on the strengths and limitations of the techniques and algorithms that are used in the generation of random keys and a new method to generate random keys is proposed using fractals. Fractals are generated using the Sierpinski triangle and fed as input for Non-Deterministic Finite Automata (NDFA) to generate an Initial Vector (IV). Trellis Coded Genetic Algorithm (TCGA) code generator generates seed value using IV as input. Pseudo-Random Key Generator (PRKG) generates a Session Key matrix (SKM) using a seed value. Images are encrypted using SKM to generate cipher images. The randomness of the TCGA code is tested using entropy measure and efficiency based on NIST Tests. SKM with high entropy value is used for image encryption. The Number of Pixel Change Rate (NPCR) and Unified Average Changing Intensity (UACI) values are used for calculating the randomness of cipher images.

Color Image Encryption Algorithm Based on a Chaotic Model Using the Modular Discrete Derivative and Langton’s Ant

In this work, a color image encryption and decryption algorithm for digital images is presented. It is based on the modular discrete derivative (MDD), a novel technique to encrypt images and efficiently hide visual information. In addition, Langton’s ant, which is a two-dimensional universal Turing machine with a high key space, is used. Moreover, a deterministic noise technique that adds security to the MDD is utilized. The proposed hybrid scheme exploits the advantages of MDD and Langton’s ant, generating a very secure and reliable encryption algorithm. In this proposal, if the key is known, the original image is recovered without loss. The method has demonstrated high performance through various tests, including statistical analysis (histograms and correlation distributions), entropy, texture analysis, encryption quality, key space assessment, key sensitivity analysis, and robustness to differential attack. The proposed method highlights obtaining chi-square values between 233.951 and 281.687, entropy values between 7.9999225223 and 7.9999355791, PSNR values (in the original and encrypted images) between 8.134 and 9.957, the number of pixel change rate (NPCR) values between 99.60851796% and 99.61054611%, unified average changing intensity (UACI) values between 33.44672377% and 33.47430379%, and a vast range of possible keys >5.8459×1072. On the other hand, an analysis of the sensitivity of the key shows that slight changes to the key do not generate any additional information to decrypt the image. In addition, the proposed method shows a competitive performance against recent works found in the literature.

Multilayer Convolutional Processing Network Based Cryptography Mechanism for Digital Images Infosecurity

Digital images can be easily shared or stored using different imaging devices, storage tools, and computer networks or wireless communication systems. However, these digital images, such as headshots or medical images, may contain private information. Hence, to protect the confidentiality, reliability, and availability of digital images on online processing applications, it is crucial to increase the infosecurity of these images. Therefore, an authorization encryption scheme should ensure a high security level of digital images. The present study aimed to establish a multilayer convolutional processing network (MCPN)-based cryptography mechanism for performing two-round image encryption and decryption processes. In the MCPN layer, two-dimensional (2D) spatial convolutional operations were used to extract the image features and perform scramble operations from grayscale to gray gradient values for the first-image encryption and second-image decryption processes, respectively. In the MCPN weighted network, a sine-power chaotic map (SPCM)-based key generator was used to dynamically produce the non-ordered pseudorandom numbers to set the network-weighted values as secret keys in a sufficiently large key space. It performs the second and first encryption processes using the diffusion method, modifying the image pixel values. Children’s headshots and medical images were used to evaluate the security level by comparing the plain and cipher images using the information entropy, number of pixel change rate, and unified averaged changed intensity indices. Moreover, the plain and decrypted images were compared to verify the decrypted image quality using the structural similarity index measurement and peak signal-to-noise ratio.

Enhanced Diffusion and Confusion Based Encryption Algorithm Using Differential Evolution and Chaotic Mapping

Encryption is critical to protecting sensitive data, especially images, against potential illegal access and breaches. The use of chaotic maps for image encryption is widespread among researchers. However, it is necessary to set up initial parameters for chaotic maps to generate random sequences. These parameters need to be selected with care. To determine the optimal initial parameters for image encryption, evolutionary optimization techniques have been used. In this paper, we propose a secure image-based communication system based on an optimized image encryption algorithm. This approach uses differential evolution optimization, which is an ideal solution for reducing convergence time when optimizing chaotic map parameters. Furthermore, the security parameters of these techniques are evaluated, including entropy, Number of Pixel Change Rate (NPCR), Unified Average Changed Intensity (UACI), and correlation coefficients. The simulation results of the proposed encryption approach by combining Arnold’s cat map, chaotic logistic map and optimization method show that the encrypted image is safe against attacks.

A New Hybrid Method for Secure Data Transmission Using Watermarking based on Fuzzy Encryption in IoT

Irregular fuzzy mapping is used for encryption and scrambling of image information in this paper. The proposed image encryption algorithm has many characteristics including large key space, few relationships between the pixels of the encrypted image, high sensitivity to the key and high security, which can effectively protect the security of the encrypted image. Therefore, a robust audio watermarking method that hides encrypted image information in the time domain is presented. After dividing the audio signal into consecutive parts, five parameters are calculated independently, including the average frequency, edge, energy, zero crossing rate, and standard deviation for different parts of the signal. With the LBP method, the encoded image is placed in different parts based on the weights determined by the fuzzy system defined on the five parameters for each part of the audio signal. Consequently, the distortion caused by hiding the watermark will not result in adverse listening effects, and the watermark will remain resistant to attacks and common audio processing. Based on the simulation results of the proposed technique under MATLAB software, it reveals the resistance of the watermark against various attacks and increasing the speed of calculations. Due to the combination of watermarking and simultaneous encoding of image information, as well as examining a large number of image evaluation criteria, including information entropy criteria and peak signal-to-noise ratio (PSNR), number of pixel change rate (NPCR), unified average changing intensity (UACI), we have been able to create a good improvement for the security of information transmission in the IoMT field.

Image encryption algorithm based on the density and 6D logistic map

One of the most difficult issues in the history of communication technology is the transmission of secure images. On the internet, photos are used and shared by millions of individuals for both private and business reasons. Utilizing encryption methods to change the original image into an unintelligible or scrambled version is one way to achieve safe image transfer over the network. Cryptographic approaches based on chaotic logistic theory provide several new and promising options for developing secure Image encryption methods. The main aim of this paper is to build a secure system for encrypting gray and color images. The proposed system consists of two stages, the first stage is the encryption process, in which the keys are generated depending on the chaotic logistic with the image density to encrypt the gray and color images, and the second stage is the decryption, which is the opposite of the encryption process to obtain the original image. The proposed method has been tested on two standard gray and color images publicly available. The test results indicate to the highest value of peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), number of pixel change rate (NPCR) are 7.7268, 50.2011 and 100, respectively. While the encryption and decryption speed up to 0.6319 and 0.5305 second respectively.

Privacy Protection of Medical Data Based on Multi-Scroll Memristive Hopfield Neural Network

Memristive Hopfield neural network (MHNN) has complex dynamic behavior, which is suitable for encryption applications. In order to ensure the information security of the medical data transmitted in Internet of Things (IoT), we propose three new MHNN models by using a non-ideal flux-controlled memristor model with multi-piecewise nonlinearity. In these models, there are complex dynamical behaviors such as coexisting attractors, multi-scroll attractors and grid multi-scroll attractors. In terms of hardware, the proposed model is implemented using field programmable gate array (FPGA). In addition, we provide a complete set of medical data sharing solution, which are helpful for the referral patients to receive timely medical treatment. The whole solution is successfully verified on Raspberry Pi, the encrypted Computed Tomography (CT) image is transmitted safely under Message Queuing Telemetry Transport (MQTT) protocol, and the CT image is subjected to basic security analysis. The results show that the ciphertext histogram is evenly distributed, the correlation between adjacent pixels is almost 0, the information entropy reaches 7.9977, and the values of number of pixels change rate (NPCR) and unified average change intensity (UACI) are 99.6078% and 33.4875%. The solution not only performs the exchange of medical data, but also protects the privacy of patients.

Protection-Enhanced Watermarking Scheme Combined With Non-Linear Systems

Communication of the images over the network calls for an approach to ensure security and ownership protection while exchanging images over the network. This paper proposes an improved blind watermarking scheme capable of offering image authentication, protection, and detachment avoidance between the watermark and its corresponding image. The proposed technique is composed of three modules; generator, protector, and resizer. The generator deals with embedding and extracting the watermark from the host image. Protector deals with encryption and decryption using a high dimensional chaotic system. And resizer deals with compressing and decompressing the watermarked image. The novelty related scientific literature is the encryption of Singular Value Decomposition (SVD) components, and watermark in a criss-cross manner using logistic map along with hyperchaotic system to achieve the confidentiality and avoid false positive problem (FPP). Whereas, embedding into RGB (red, green, blue components) is centered on singular value decomposition and level-2 Discrete Wavelet Transform. The joint operation is performed at sender’s side and receiver’s side, i.e., encryption, embedding, and compression is performed at sender’s side whereas decompression and decryption procedures are performed at the receiver’s side. Additionally, compressing the data reduces the higher bandwidth requirements. The performance of the proposed scheme is based on subjective and objective evaluation. Experimental results such as PSNR (peak signal-to-noise ratio), NC (normalized correlation), BER (bit error rate), CR (compression ratio), NPCR (number of pixel change rate), and SSIM (structural similarity index) indicate that the proposed technique approaches the standard main level.

Highly Efficient Security Level Implementation in Radiation-Tolerance FPGA Using a Combination of AES Algorithm and Hamming Code: LST-SW Case

Nowadays, Satellite remote sensing and especially earth observation satellites require improvement when implementing an algorithm using reconfigurable hardware in terms of efficiency, performance, and security level. Furthermore, the transmission of the computed data from the earth observation satellite to the ground station is subject to potential attacks, and data can be corrupted during transmission. The land surface Temperature algorithm is an essential factor that can be extracted from the earth observation satellite. In this paper, we proposed a secure land surface temperature implementation by combining the advanced encryption algorithm and Hamming code implemented on radiation-tolerant Virtex-4QV field programmable gate array (FPGA). The iterative looping technique was used to implement the Advanced Encryption Standard (AES) algorithm with the aim of achieving high throughput and high security levels. The results showed that the proposed hardware implementation consumes 3319 Slices and 2 BRAMs while achieving higher throughput of 1854.82 Mbps. Moreover, we have evaluated the efficiency of the suggested cryptosystem by exploiting security measurement analysis such as Histogram, correlation coefficient, entropy, number of pixels change rate (NPCR), and unified averaged changed intensity (UACI). The proposed cryptosystem results prove the efficiency in terms of hardware consumed and high-security level. This implementation may be utilized, proposed, and even configurable for any earth observation satellites, including nano- and pico-CubeSats since we employed radiation-tolerant FPGA.

Encryption of medical images using a chaotic multi-level scheme

Encryption of medical images is an essential component of the overall security infrastructure of the healthcare industry. Within the current context of digital technology for the storage, transmission, and evaluation of medical data, teleradiology is becoming an increasingly important field. A chaos-based multilevel encryption and decryption scheme is proposed for use with medical images in this research effort. When contrasted with traditional single-level encryption, the logistic chao-based multilevel encryption and decryption were determined to be superior in terms of their effectiveness. The pixel information of the photos is used, along with a permutation method and Xor operations, to construct the secret keys for the images. Metrics such as entropy, correlation measures, the number of pixels change rate, and the unified average changing intensity was utilised during the performance validation process. The proposed strategy is secure against common cryptographic attacks. ADNI Dataset is used for testing and training and contains 2660 MRI images of the human brain.