Number Of Pixel Change Rate Research Articles

Image Encryption Using High-Speed Scrambling and ‎Modular Arithmetic

With the enormous growth and advancement of the computer industry, it is critically necessary to transmit a large amount of encrypted multimedia data to prevent third parties from attacking one's privacy or misbehaving. This study proposes a new encryption strategy for preserving original images. It is highly effective and has been shown to be resilient against impulsive noise and loss of data. At first, some random data is entered within the perimeter of the image. Then, three rounds of high-speed scrambling and adaptive diffusion for pixels are carried out to mix the contiguous pixels at random and distribute the newly placed data throughout the image. The suggested encryption method can be used to encrypt original images in any form of representation directly. We offer a particular operation to carry out adaptive diffusion for pixel modulo arithmetic. The results of encryption are evaluated using the histogram, which shows a near-zero correlation with a Number of Pixel Change Rate (NPCR) of 099.624, a Unified Average Change Intensity (UACI) of 033.577, and an average entropy of 7.9993. The proposed method can accomplish much better speed and adapt better to impulse noise and loss of data interference than several conventional and cutting-edge encryption methods.

Global Exponential Synchronization of Delayed Quaternion-Valued Neural Networks via Decomposition and Non-Decomposition Methods and Its Application to Image Encryption

With the rapid advancement of information technology, digital images such as medical images, grayscale images, and color images are widely used, stored, and transmitted. Therefore, protecting this type of information is a critical challenge. Meanwhile, quaternions enable image encryption algorithm (IEA) to be more secure by providing a higher-dimensional mathematical system. Therefore, considering the importance of IEA and quaternions, this paper explores the global exponential synchronization (GES) problem for a class of quaternion-valued neural networks (QVNNs) with discrete time-varying delays. By using Hamilton’s multiplication rules, we first decompose the original QVNNs into equivalent four real-valued neural networks (RVNNs), which avoids non-commutativity difficulties of quaternions. This decomposition method allows the original QVNNs to be studied using their equivalent RVNNs. Then, by utilizing Lyapunov functions and the matrix measure method (MMM), some new sufficient conditions for GES of QVNNs under designed control are derived. In addition, the original QVNNs are examined using the non-decomposition method, and corresponding GES criteria are derived. Furthermore, this paper presents novel results and new insights into GES of QVNNs. Finally, two numerical verifications with simulation results are given to verify the feasibility of the obtained criteria. Based on the considered master–slave QVNNs, a new IEA for color images Mandrill (256 × 256), Lion (512 × 512), Peppers (1024 × 1024) is proposed. In addition, the effectiveness of the proposed IEA is verified by various experimental analysis. The experiment results show that the algorithm has good correlation coefficients (CCs), information entropy (IE) with an average of 7.9988, number of pixels change rate (NPCR) with average of 99.6080%, and unified averaged changed intensity (UACI) with average of 33.4589%; this indicates the efficacy of the proposed IEAs.

Securing blockchain-enabled smart health care image encryption framework using Tinkerbell Map

IoT enables the emergence and implementation of smart devices to address real-world problems and challenges. Today we are surrounded by various smart devices, such as smart phones, smart homes, smart cars, smart televisions, and smartwatches that assist us in making our lives easier and smoother. IoT is a conglomeration of multiple technologies at various layers to impart the best of ubiquitous and pervasive computing to deliver several benefits in a variety of application sectors such as medicine, agriculture, and industry. In an IoT setting, blockchain technology is used for addressing security challenges and eradicating third-party participation. Utilizing public networks for storing or transmitting health care images poses risks of eavesdropping, data breaches, and unauthorized access. Before uploading medical data to the decentralized network, encryption is required to prevent unauthorized access. The aim of this study is to integrate technologies to ensure transactions are conducted safely and securely. We proposed an IoT-Blockchain system based on chaos encryption scheme using Tinkerbell mapping to ensure medical data integrity and authenticity. The suggested approach is examined to assess performance parameters such as, key space analysis, key sensitivity analysis, Information Entropy (IE), histogram, correlation of adjacent pixels, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Structural Similarity Index (SSIM). These findings demonstrated that the suggested method is extremely efficient in avoiding security breaches and guaranteeing information integrity.

Optimized data management with color multiplexing in QR codes

This study integrates colorimetry and computation by identifying their commonalities to develop a novel encryption system centered around color, specifically using QR codes. We propose an approach that multiplexes QR codes of varying colors, each containing distinct information. A key is generated to encapsulate user-specific data and identify the QR code with authentic information. We develop serverless architectures to facilitate rapid encryption and decryption processes. The system’s performance and efficiency are evaluated through two architectures: a sequential system implemented on Google Colab and a distributed system utilizing AWS Lambda serverless architecture. Metrics such as NPCR (Number of Pixels Change Rate), UACI (Unified Average Changing Intensity) and key space analysis, indicative of the system’s robustness, are analyzed according to existing literature. In addition, the cost of this serverless technology is evaluated in comparison to cloud and local. Our findings demonstrate that the serverless architecture offers a viable and efficient solution for coding. The implications of this research extend across various sectors, including defense, healthcare, and everyday digital interactions, presenting a scalable and secure alternative for data encryption and communication.

Image encryption algorithm based on multiple chaotic systems and improved Joseph block scrambling

Abstract With the rapid development of digital information technology, images are increasingly used in various fields. To ensure the security of image data, prevent unauthorized tampering and leakage, maintain personal privacy, and protect intellectual property rights, this study proposes an innovative color image encryption algorithm. Initially, the Mersenne Twister algorithm is utilized to generate high-quality pseudo-random numbers, establishing a robust basis for subsequent operations. Subsequently, two distinct chaotic systems, the autonomous non-Hamiltonian chaotic system and the tent-logistic-cosine chaotic mapping, are employed to produce chaotic random sequences. These chaotic sequences are used to control the encoding and decoding process of the DNA, effectively scrambling the image pixels. Furthermore, the complexity of the encryption process is enhanced through improved Joseph block scrambling. Thorough experimental verification, research, and analysis, the average value of the information entropy test data reaches as high as 7.999. Additionally, the average value of the number of pixels change rate (NPCR) test data is 99.6101%, which closely approaches the ideal value of 99.6094%. This algorithm not only guarantees image quality but also substantially raises the difficulty of decryption.

Chaos based image encryption scheme to secure sensitive multimedia content in cloud storage

Cloud computing offers a variety of on-demand services to users and has gained significant prominence in the contemporary era. The security of information stored in cloud data centers has become a central concern, especially for sensitive data like medical images, videos, and multimedia content that require heightened protection when stored in data centers. Cloud users have a responsibility to ensure the security of their data through strategic measures. Focusing on maintaining the privacy of images stored in the cloud, this research introduces an innovative image encryption technique that is based on a modified Skew Tent chaotic map. The suggested modification to the chaotic map includes combining the Skew Tent map with both the sine trigonometric function and perturbation technology. This results in enhanced randomness, more intricate dynamical behavior, a broader chaotic range, and increased sensitivity to initial values in contrast to alternative chaotic maps. The incorporation of this adapted map into a stepwise procedure, involving two rounds of permutation followed by diffusion, effectively accomplishes image data encryption for cloud storage systems. These consecutive operations collectively enhance the encryption method’s randomness and robustness. Through simulations conducted using Cloudsim, the cipher-image exhibits a uniform distribution and achieves a commendable information entropy score of 7.996749. The encryption algorithm significantly reduces correlation coefficients from 1 in the original image to 0 in the encrypted image, while maintaining NPCR (Number of Pixel Change Rate) and UACI (Unified Average Changing Intensity) values within the critical range. Additionally, both theoretical analysis and practical evaluations confirm the algorithm’s resilience against exhaustive, occlusion, and classical attacks. Moreover, extending this encryption framework to video data, a novel video encryption approach is proposed.

A Comprehensive Review on Image Encryption Techniques using Memristor based Chaotic System for Multimedia Application

Image encryption is one of the most widely used techniques for securing images in trusted and unrestricted public media. However, the drawback is weak security in chaotic encryption algorithms, small key space and hardware implementation complexities. Various appropriate encryption algorithms have been carried out for secure image transmission; it becomes a critical issue to protect image integrity, confidentiality and authenticity. To overcome these issues, this article examines several existing memristor-based image encryption algorithms with various chaotic maps. As a result, this research aims to deliver comprehensive literature on image encryption techniques through memristor to help the researchers. Finally, this survey provides all vital literature on the current image encryption techniques with their benefits, drawbacks, developments, and future directions. We also give a general guideline about cryptography. We conclude that all methods are helpful for real-time image encryption. A comparison has been made between many image processing approaches (conventional and memristor) based on metrics such as the number of pixels change rate (NPCR) with the value of 0.9986, histogram, entropy (7.9993), unified average varying intensity (UACI) achieves the value as 0.4996, energy consumption as 0.32pJ and time complexity as 0.9s. The experimental results of various approaches, key sensitivity and statistical analysis revealed that the survey of memristor-based image encryption schemes provides an effective way to secure image transmission in real-time application.

Reconfigurable Image Confusion Scheme Using Large Period Pseudorandom Bit Generator Based on Coupled-Variable Input LCG and Clock Divider

This paper presents a reconfigurable image confusion scheme, which uses Linear Congruential Generators (LCGs)-based Pseudorandom Bits Generator (PRBG). The PRBG is based on the variable input-coupled LCG with a reconfigurable clock divider. The proposed algorithm encrypts the input image up to four times successively using different random sequences in every attempt. This new scheme aims to efficiently extract statistically strong pseudorandom sequences from a proposed PRBG with a large keyspace and simultaneously increase the security level of the encrypted image. This PRBG was initially designed on Virtex-5 (XC5VLX110T), Virtex-7 (XC7VX330T) and Artix-7 (XC7A100T) Field Programmable Gate Arrays (FPGAs). The statistical properties of the proposed PRBG for four different configurations are verified by the National Institute of Standards and Technology (NIST) tests. Thereafter, a reconfigurable encryption/decryption algorithm that uses the proposed PRBG is developed for secure image encryption. The encryption process was accomplished using the MATLAB tool after obtaining the PRBG keys from the FPGA. To show the quality and strength of the encryption process, security analysis [correlations and Number of Pixels Change Rate (NPCR)] is performed. Security analysis results are compared with the conventional encryption algorithm to show that the developed reconfigurable encryption scheme provides better results in security tests.

Perbandingan Algoritma SIMON dan SPECK Dalam Pengamanan Citra Digital

Cryptography is a data security technique by encoding data that is to be kept secret so that the original meaning of the data can no longer be understood. SIMON and SPECK are modern cryptographic algorithms issued by the National Security Agency (NSA). SIMON and SPECK are said to be algorithms that are known for their efficiency and strong security. This research will compare the performance of the SIMON and SPECK algorithms in securing digital images. Comparisons were made by testing time performance, changes in file size, and the level of randomness of image files using the Unified Average Changing Intensity (UACI) and Number of Pixels Change Rate (NPCR) metrics. The research results show that the average encryption and decryption time required by the SIMON algorithm is greater when compared to the SPECK algorithm. The image file size resulting from encryption using the SIMON and SPECK algorithms both increased by 24% from the original image. The level of randomness of the resulting image based on the UACI value obtained using the SIMON algorithm was found to be an average of 19.65%, while the UACI value obtained using the SPECK algorithm was an average of 20.94%. This shows that there is a significant change in intensity between the original image and the encrypted image. However, not all pixels in the encrypted image change when compared to the original image, this is shown by the NPCR value obtained from the SIMON and SPECK algorithm encrypted image, with average results of 49.98% and 50.17%.

An approach for encrypting images using a four-dimensional logistic map

Encrypting image transmission has been one of the most complex challenges with communication technology ever. Millions of people utilize and share photographs via the internet for personal and professional purposes. One approach to secure picture transfer over the network is to use encryption techniques to transform the original picture into an unreadable or garbled version. Several novel and encouraging possibilities for creating secure Image data encryption techniques are presented by cryptographic algorithms grounded in chaotic logistic theory. Developing a foolproof method for encrypting both black-and-white and color image is the primary focus of this work. Both grayscale and color images can be encrypted using the keys generated by combining the chaotic logistic with the image's density in the first stage of the proposed system's encryption process. The original image can then be recovered in the second stage, which is the inverse of the encryption process. Two publicly available standard grayscale and color photographs were analyzed to evaluate the suggested approach. Peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), and number of pixels change rate (NPCR) were found to be 6.6268, 51.3011, and 100, respectively, according to the test findings.

A Hyper-chaotic Medical Image Encryption with Optimized Key Value

This article delves into a medical image encryption/decryption method based on hyper chaotic dynamics and genetic algorithms. The proposed algorithm boasts simplicity in implementation, featuring straightforward operations that render it well-suited for real-time applications while elevating its security measures. Leveraging the sensitivity of chaotic behaviour to initial conditions, a genetic algorithm is employed to select optimal initial conditions for the 5D multi-wing hyper-chaotic system. Initially, a secret key generation method based on the input image is applied, followed by stages of diffusion and encryption utilizing the chaotic system. The secret key undergoes optimization through a genetic algorithm, considering specific parameters within the encrypted image as encryption factors. Subsequently, the encrypted image with the optimized secret key is finalized, serving as the basis for decrypting the cipher image. The proposed method undergoes simulation, testing, and comparison against other image encryption algorithms. Both experimental results and computer simulations affirm the robustness of this cryptographic system, showcasing a significant key space value (2^256), high key sensitivity (Number of Pixels Change Rate: NPCR > 99.55%, Unified Average Changing Intensity: UACI > 33.37%), and its ability to fend off various types of attack.

Evaluations of Crypto-System AES Using Multiple Bloc Ciphering Mode

Cryptography, a scientific field that has existed even before the beginning of computer science. This article looks at the development symmetric crypto-system, which falls within the framework of image security, by Advanced Encryption Standard (AES- Advanced Encryption Standard) algorithms. AES algorithm is not integrity protected. Cryptanalysis could use modified encrypted image of each ciphered bloc for generating oracle and getting the key. A new crypto-system uses hash function named AES-GCM (Advanced Encryption Standard-) for solving this problem. Using Galois Counter Mode (GCM) combined with Secure Hash Algorithm 256 bits (SHA-256) or BLAKE2s hash function, the old mode of ciphering like: Cipher FeedBack (CFB), Output FeedBack (OFB), Cipher Block Chaining (CBC), Electronic Codebook Block (ECB) and CounTeR (CTR) mode encryption, will increase the security level at confidentiality and integrity. In this article, robustness of the crypto-system will be evaluated by multiple criteria, indeed the statistical analysis, sensitivity measurement and performance measurement. For the statistical analysis, the histogram is flat and the correlation between adjacent pixel is not linear for the encrypted image. The relation between clear image and encrypted image doesn’t exist. For the sensitivity analysis, Number of Pixel Changing Rate (NPCR) and Unified Averaged Changed Intensity (UACI) permit to avoid differential attack of the crypto-system. The two values are respectively near 99% and 30%. For performance measurement, the similarity of the decrypted image and original image will be tested. The Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are equals of infinity and zero. The decrypted image and original image are the same. The integrity of the image on the crypto-system will be evaluated by modifying one bit of the encrypted image. The decryption process doesn’t give decrypted image and show that the tag value is incorrect.

Multiobjective Optimization of Chaotic Image Encryption Based on ABC Algorithm and DNA Coding

As digital communication and storage continue to expand, the protection of image privacy information becomes increasingly critical. To safeguard sensitive visual information from unauthorized access, this paper proposes a novel image encryption scheme that integrates multiobjective Artificial Bee Colony (ABC) optimization algorithm and DNA coding. Multiple evaluation metrics including correlation relationship, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), and information entropy are collaboratively optimized by the ABC algorithm. The proposed method begins with the application of the SHA-256 algorithm to generate keys and random sequences using chaotic systems. These sequences are then employed for shuffling, DNA coding, decoding, and diffusion, generating initial encrypted images. Subsequently, the encrypted images serve as individuals within the ABC algorithm to determine optimal parameters of the chaotic systems and the best ciphertext image. Simulation experiments demonstrate that the ciphertext images achieved excellent results in information entropy, pixel correlation coefficient, NPCR, and UACI. The integration of the multiobjective ABC optimization algorithm with DNA coding in our proposed image encryption scheme results in heightened security, as evidenced by superior performance in various metrics.

Multi‐chaotic maps and blockchain based image encryption

SummaryThe vast technological developments make data transmission more frequent over networks. So, the data needs to be secured and for that reason, there is a requirement to develop an effective encryption model. This article proposes a novel image encryption model using multi‐chaotic maps and blockchain (MCBE). Chaotic maps have been used in encryption models as chaotic maps have the properties of randomness, and non‐periodicity that get utilized in improving the efficiency of an encryption model. Logistic and tent maps have been employed as multi‐chaotic maps to make the encryption process effective in this work. A logistic map has a simple structure and is easily implementable but has some drawbacks like small keyspace. Keyspace and randomness are enhanced by using a tent map along with a logistic map. The proposed MCBE methodology applies to grayscale or colored images having different file formats and sizes. Initially, in the confusion phase, the permutation of the original image is performed based on a random permutation that changes the original image pixel's position. The encryption model applies multi‐chaotic maps, row‐wise and column‐wise in the diffusion phase to promote the efficiency of the encryption model. Finally, blockchain has been implemented using the SHA‐256 hash function to obtain the encrypted image that enhances the security by increasing the keyspace, to resist brute force attacks. The evaluation performance of the MCBE has been analyzed against various attacks namely statistical attacks, differential attacks, NIST randomness test, noise, and cropping attacks. The evaluated keyspace is which has high key sensitivity with a correlation of encrypted images close to 0. Maximum achieved entropy value of 7.9998, SSIM value between original and encrypted images nearby 0 confirms the dissimilarity. The Number of Pixels Change Rate (NPCR) value of 99.62%, and the value of Unified Average Changed Intensity (UACI) value of 33.54% are within the specified standard range. The calculated correlation coefficient, NPCR, and UACI values have been compared with the existing algorithms, and the results show that the proposed MCBE methodology has better performance than the other state‐of‐the‐art methods. The experimental results indicate that the chaotic ranges generated by multi‐chaotic maps and the SHA‐256 hash function improve the keyspace and security of the encryption model confirming the efficacy of the proposed model MCBE.

An innovative image encryption algorithm enhanced with the Pan-Tompkins Algorithm for optimal security

This study introduces a cutting-edge image encryption algorithm aimed at elevating security standards. The Pan-Tompkins Algorithm (PTA) for key generation is proposed for the first time in this study. Additionally, employing steganography through the Least Significant Bit (LSB) method for embedding keys within the encrypted image enhances secure key distribution, thereby fortifying the encryption process. On the other hand, the integration of advanced algorithms, such as Zigzag scanning, the Affine Image Encryption Algorithm (AA), and the Vigenere Image Encryption Algorithm (VA), constitutes the fundamental innovation of the proposed image encryption algorithm. The proposed algorithm is named PanAAVA:Affine Algorithm and Vigenere Algorithm Encryption with PTA-Based Key Generation. The PanAAVA algorithm ensures unparalleled security by encrypting the positions and values of pixels using AA and VA. Notably, using PTA for key generation marks a distinctive and new key generation method feature of the algorithm. To assess the effectiveness of the PanAAVA, a comprehensive comparative analysis is conducted against well-established encryption methodologies, including Lena, Baboon, Airplane, and Pepper.The PanAAVA demonstrates exceptional proficiency in histogram analysis. The PanAAVA demonstrates a Unified Average Changing Intensity (UACI) of 33.4044%. Additionally, the Number of Pixels Change Rate (NPCR) is measured at 99.7442%, showcasing the algorithm’s effectiveness in inducing significant pixel changes. The proposed algorithm’s Mean Square Error (MSE) is calculated at 3.20679E5%. The proposed algorithm’s Peak Signal to Noise Ratio (PSNR) is recorded at 9.512475. The Key Space Size of the proposed algorithm is measured at 2209. Regarding correlation analysis, the PanAAVA achieves a high correlation score of 7.9996. The proposed algorithm successfully passes the National Institute of Standards and Technology (NIST) analysis, demonstrating a remarkably strong correlation close to 0 and a Structural Similarity Index Measure (SSIM) of 0.9977. Furthermore, regarding quantum communication, the proposed algorithm maintains stable key rates of 47.5 ± 0.8 kHz during the day and 50.9 ± 0.7 kHz at night. Additionally, PanAAVA achieves low Quantum Bit Error Rate (QBER) values of 4.77 ± 0.02, ensuring reliable and secure communication. The PanAAVA also demonstrates robust asymmetries at 49.81 ± 0.02 and 50.14 ± 0.03 for a crystal length of 20 mm. highlighting PanAAVA’s adaptability and effectiveness in different scenarios. PanAAVA outperforms other encryption algorithms concerning performance measurements and comparisons. In conclusion, the PanAAVA emerges as a beacon of superior security capabilities and innovation in image encryption, showcasing the potential to redefine standards in the field.

Blockchain based medical image encryption using Arnold’s cat map in a cloud environment

Improved software for processing medical images has inspired tremendous interest in modern medicine in recent years. Modern healthcare equipment generates huge amounts of data, such as scanned medical images and computerized patient information, which must be secured for future use. Diversity in the healthcare industry, namely in the form of medical data, is one of the largest challenges for researchers. Cloud environment and the Block chain technology have both demonstrated their own use. The purpose of this study is to combine both technologies for safe and secure transaction. Storing or sending medical data through public clouds exposes information into potential eavesdropping, data breaches and unauthorized access. Encrypting data before transmission is crucial to mitigate these security risks. As a result, a Blockchain based Chaotic Arnold’s cat map Encryption Scheme (BCAES) is proposed in this paper. The BCAES first encrypts the image using Arnold’s cat map encryption scheme and then sends the encrypted image into Cloud Server and stores the signed document of plain image into blockchain. As blockchain is often considered more secure due to its distributed nature and consensus mechanism, data receiver will ensure data integrity and authenticity of image after decryption using signed document stored into the blockchain. Various analysis techniques have been used to examine the proposed scheme. The results of analysis like key sensitivity analysis, key space analysis, Information Entropy, histogram correlation of adjacent pixels, Number of Pixel Change Rate, Peak Signal Noise Ratio, Unified Average Changing Intensity, and similarity analysis like Mean Square Error, and Structural Similarity Index Measure illustrated that our proposed scheme is an efficient encryption scheme as compared to some recent literature. Our current achievements surpass all previous endeavors, setting a new standard of excellence.

Image security using steganography and cryptography with sweeping computational ghost imaging

A sweeping computational ghost imaging (SCGI)-based encryption system is intended for increased data security and speedier data transport. SCGI is combined with steganography and cryptography processes in this system. SCGI requires fewer shots, resulting in faster image capture, transmission, encryption, and decryption. This strategy also results in smaller, more compact data packages and higher bitrates. Least significant bit (LSB) uses steganography to conceal the hidden picture. In the case of Rivest–Shamir–Adleman (RSA) encryption, public and private keys are generated via a one-way function based on bucket values. Encryption is performed on two levels, with an asymmetric approach divided into three sub-items that significantly increase encryption. Surprisingly, the method uses fewer pictures for image reconstruction, resulting in faster image reconstruction. SCGI promises applications in an extensive number of data encryption sectors since this technology leads to smaller data packages and higher bitrates. The presented approach is examined using the number of pixel change rate (NPCR), normalized root mean square (NRMS), peak signal-to-noise ratio (PSNR), and correlation coefficient (CC), which indicates constant encryption improvement. We experimentally and situationally demonstrate our findings under eavesdropping, which prove the resistance and robustness of our methods. In optimal settings, this innovation enhances encryption by up to 90% when compared to traditional encryption methods.

A Hybrid Cryptosystem Incorporating a New Algorithm for Improved Entropy.

Today, safeguarding sensitive content through encryption is crucial. This work presents a hybrid cryptosystem for images that employs both asymmetric and symmetric encryption. The asymmetric component involves applying the Diffie-Hellman protocol and the ElGamal cryptosystem to securely transmit two constants. These constants are necessary for the symmetrical aspect to generate dynamic permutations, substitution boxes, and round keys. Following an encryption process with fourteen rounds, the encrypted images are processed by an algorithm proposed to enhance entropy, a critical metric for assessing encryption quality. It increases the frequencies of the basic colors to achieve a histogram closely resembling a uniform distribution, but it increases the image size by approximately 8%. This improves the entropy values achieved by the hybrid cryptosystem, bringing them remarkably close to the ideal value of 8.0. In specific instances, the entropy values were elevated from 7.99926 to 8.0. The proposed method exhibits resilience against various attacks, including differential, linear, brute force, and algebraic attacks, as evaluated through the entropy, correlation, goodness of fit, Discrete Fourier Transform (DFT), Number of Pixels Change Rate (NPCR), Unified Average Changing Intensity (UACI), Avalanche Criteria (AC), contrast, energy, and homogeneity. Further, encrypted images are subjected to noise attacks ranging from 20% to 50% noise, including additive, multiplicative, occlusion noise, as well as the newly introduced χ2 noise. The noise damage is quantified using the proposed Similarity Parameter (SP), and a 3 × 3 median filter is employed to enhance the visual quality.

An optimized chaotic S-box for real-time image encryption scheme based on 4-dimensional memristive hyperchaotic map

As digital products communicate over public networks, digital image security becomes essential. Despite advancements in encryption technology, protecting data from secure images remains a complex computational issue that necessitates using an encrypted environment to protect data transmitted from devices over networks. Encryption is critical for protecting sensitive information, especially images, from unauthorized access or failure. Image encryption is distinct from text encryption. Images contain extensive data with high redundancy and a high correlation between nearby pixels, making them difficult to process with traditional technology. In recent decades, chaos maps have become popular in the crypto community. This work proposes a new encryption technology based on chaotic map substitution boxes (S-box) and cellular automata (CA) to address the frequent challenges in chaotic encryption methods. To address the inadequate randomness provided by the 1D chaotic map, this work presented a 4D memristive hyperchaos with a more excellent chaotic range, increased uncertainty, and ergodicity as an alternative to the software-based approach, which is vulnerable and offers low throughput. The suggested encryption technique was implemented on an Intel Cyclone IV EP4CE115F29C7 FPGA. It is less prone to tampering and has a better throughput. This suggested encryption scheme employs 1384 LEs. In comparison to traditional algorithms, the suggested Number of Pixels Change Rate (NPCR) (99.9706%), unified averaged changed intensity (UACI) (33.3956%), and information entropy (IE) (7.984) accomplish more effective. Statistical studies such as IE, histogram, correlation, peak signal-to-noise ratio (PSNR), differential analysis such as NPCR and UACI, and noise attack analyses are employed to validate the suggested encryption design. Regarding security, the suggested hybrid method outperforms conventional algorithms while protecting image quality.

Color image encryption based on discrete memristor logistic map and DNA encoding

This paper proposes a color image encryption scheme with new features based on two-dimensional discrete memristor logistic map (2D-MLM), Deoxyribonucleic acid (DNA) encoding and multi-wing hyperchaotic systems. Firstly, the discrete memristor map and four-wing hyperchaotic system are used to generate various pseudo-random sequences. Secondly, the original image is processed in blocks, and DNA encoding and operation are performed on the sub-block image using multiple pseudo-random sequences. Finally, combining the pseudo-random sequence to diffuse the sub-block image and DNA decoding, we can get the encrypted image. The scheme generates a one-time key for each image, and uses multiple different sub-keys to increase the key space. The use of diverse pseudo-random sequences for image scrambling effectively avoids the security risks associated with using a single chaotic sequence. The key space of this algorithm reaches 2425, the information entropy of the ciphertext image is 7.9993, the number of pixels change rate (NPCR) and the uniformed average change intensity (UACI) reach 99.6095 % and 33.5089 %, and the inter-pixel correlation is close to zero. The simulation results prove that the proposed algorithm has good security against many potential attacks.