Model of Pseudo-Random Sequences Generated by Encryption and Compression Algorithms

We propose a new and efficient method to develop secure image‐encryption techniques. The new algorithm combines two techniques: encryption and compression. In this technique, a wavelet transform was used to decompose the image and decorrelate its pixels into approximation and detail components. The more important component (the approximation component) is encrypted using a chaos‐based encryption algorithm. This algorithm produces a cipher of the test image that has good diffusion and confusion properties. The remaining components (the detail components) are compressed using a wavelet transform. This proposed algorithm was verified to provide a high security level. A complete specification for the new algorithm is provided. Several test images are used to demonstrate the validity of the proposed algorithm. The results of several experiments show that the proposed algorithm for image cryptosystems provides an efficient and secure approach to real‐time image encryption and transmission.

With the rapid growth of the volume of image data, the burden of storage and transmission has increased dramatically. However, current algorithms face challenges in balancing compression efficiency with security. In this paper, a novel algorithm for image compression and encryption utilizing an optimized BP neural network is proposed. First, the fireworks algorithm (FWA) is employed to optimize the initial weights of a BP network, bolstering image compression efficiency and reconstruction quality. Second, a variable-parameter chaotic system is constructed by combining Logistic-Tent and Chebyshev maps. Meanwhile, the pseudo-random sequences are generated by a variable-parameter chaotic system for scrambling and diffusion. Subsequently, a multi-level global-local scrambling mechanism is introduced to disrupt the statistical properties of the image. Finally, a Gray Code-based mutation-diffusion strategy is implemented to achieve encryption. Experimental results indicate that the encryption algorithm exhibits strong robustness in terms of histogram analysis, information entropy, key space, and attack resistance. At identical compression ratios, the proposed scheme proves superior to BP neural networks, delivering higher reconstruction quality for high-fidelity image recovery.

With the advancement of multimedia technology and coming of big data era, the size of image data is significantly increased. However, the traditional image encryption methods cannot solve the emerging problems of efficient compression. To settle with this challenge, an effective content-adaptive image compression and encryption method based on compressive sensing and double random phase encoding (DRPE) is proposed in this paper. The original image is converted to one low-frequency part and three high-frequency parts by DWT and then permutated by sorting-based chaotic sequences. Afterward, a novel measurement matrix optimization algorithm based on adaptive step size is presented to measure the high-frequency components. To enhance the security of the scheme, the DRPE, quantization, and diffusion are successively performed on the complex matrix composed of the shuffled low-frequency component and three measurement value matrices to obtain the cipher image. Logistic-Sine chaotic system is utilized to produce the chaotic keystreams for the encryption process, and its system parameter and initial value are determined by the information entropy of the plain image and external key parameters, so that the proposed cipher can withstand known-plaintext and chosen-plaintext attacks effectively. Numerical experiments demonstrate the effectiveness of the proposed image compression and encryption algorithm.

Numerous image encryption schemes are hindered by weak correlations with plaintex images, inadequate image reconstruction quality, and inefficient transmission and storage. To address these problems, this paper proposes an image compression–encryption algorithm that combines a three-dimensional discrete chaotic system, Josephus circle and compression perception. First, a new three-dimensional discrete hyperchaotic system is constructed, utilizing a hash function to generate the initial value of the chaotic system, through which the measurement matrix and the sequences required for the encryption process are constructed. An encryption algorithm based on chaotic sequence and Josephus circle is designed. Finally, the proposed compressed encryption algorithm is simulated and tested, and the results of experimental tests indicate that the proposed algorithm provides robust security and high-quality reconstruction performance.

A considerable portion of research activities in computer science heavily relies on the process of benchmarking, e.g., to evaluate a hypothesis in an empirical study. The goal is to reveal how a set of independent variables (factors) influences one or more dependent variables. With a vast number of factors or a high amount of factors' values (levels), this process becomes time- and energy-consuming. Current approaches to lower the benchmarking effort suffer from two deficiencies: (1) they focus on reducing the number of factors and, hence, are inapplicable to experiments with only two factors, but a vast number of levels and (2) being adopted from, e.g., combinatorial optimization they are designed for a different search space structure and, thus, can be very wasteful. This paper provides an approach for benchmark reduction, based on adaptive instance selection and multiple linear regression. We evaluate our approach using four empirical studies, which investigate the effect made by dynamic voltage and frequency scaling in combination with dynamic concurrency throttling on the energy consumption of a computing system (parallel compression, sorting, and encryption algorithms as well as database query processing). Our findings show the effectiveness of the approach. We can save 78% of benchmarking effort, while the result's quality decreases only by 3 pp, due to using only a near-optimal configuration.

Joint encryption and compression method not only ensure the uniformity of the algorithm but also can enhance the security of algorithm, so it have very important practical significance.This paper studies the over complete dictionary of DCT and OMP algorithm,uses the two kinds of common chaos mapping and learns China remainder theorem. Then one joint image compression and encryption algorithms using chaos map, sparse decomposition and Chinese remainder theorem is proposed to realize image compression and encryption.The experimental results show that the algorithm realizes information transmission requirements in security and efficiency, and achieves the desired requirements.

To enhance image privacy protection and reduce storage space, this paper proposes an image compression and encryption algorithm that combines compressed sensing, Hachimoji DNA coding, and a 7D hyperchaotic system. The algorithm processes the high-frequency and low-frequency parts after the wavelet transform separately. Sparse high-frequency information is compressed by low-compression measurement. The low-frequency part uses block-compressed sensing, and only a small amount of data is needed to reconstruct a high-quality image. In addition, the measurement matrix is constructed by chaotic sequence, which reduces the demand for memory and transmission bandwidth. To protect compressed data, this paper also presents an image encryption algorithm based on Hachimoji DNA dynamic coding and Joseph dynamic traversal. The algorithm first uses Joseph traversal to disturb the bit position of each pixel dynamically and then implements Hachimoji DNA dynamic coding. At the same time, a new Joseph bidirectional dynamic scrambling-diffusion algorithm is proposed, which gives the encrypted image a uniform grayscale histogram, high information entropy, and sensitivity to resist various attacks effectively.

Leading Zero Count (LZC) plays a crucial role in arithmetic and logic operations (ALU) within digital circuits, both sequential and combinational. LZC refers to the process of determining the number of consecutive leading zeros in a binary number. Both combinational and sequential LZC circuits find extensive usage in digital signal processing tasks, where quick and accurate determination of leading zeros is essential for various operations like normalization, filtering and feature extraction. Furthermore, they are integral components in hardware implementation of algorithms for data compression and encryption, contributing to enhanced efficiency and performance. The design principles, implementation strategies and applications of leading zero count in both combinational and sequential settings, highlighting their significance in modern digital systems. The LZC system is simulated and synthesized using Xilinx ISE tool and implemented on Artix-7 FPGA.

Lossless image compression and encryption using SCAN

Purpose: increasing the cryptographic strength level of the pseudo-random sequence generation function based on the «Kuznechik» encryption algorithm. Research methods: methods for constructing pseudo-random sequence generators using a strong cryptographic algorithm as a generation function in accordance with the recommendations of NIST SP 800-90. Methods of probability theory and mathematical statistics (statistical hypothesis testing, Pearson’s criterion), methods for estimating the entropy of a random process. Results: а method for development of the main component of the deterministic generator – the function for generating pseudo-random sequences based on the «Kuznechik» encryption algorithm (Russian encryption standard GOST R 34.12-2015) due to a number of the original algorithm modifications is proposed. Features of the algorithm allow to use it in a mode that combines the advantages of the well-known encryption modes of block ciphers (OFB and CTR encryption modes). A procedure for generating round keys and other modifications of the algorithm that increase its security while maintaining its performance have been developed and implemented. The generator operation was evaluated on the basis of the statistical properties of the output sequences (NIST SP 800-22 tests), Pearson’s χ2 criterion, and min-entropy (NIST 800-90B tests). According to the characteristics mentioned above, the proposed generation function is comparable with the reference version based on GOST 34.12-2015 «Kuznechik», but exceeds it in terms of security.

In every system of security, to keep important data confidential, we need a high degree of protection. Steganography can be defined as a way of sending confidential texts through a secure medium of communications as well as protecting the information during the process of transmission. Steganography is a technology that is used to protect users' security and privacy. Communication is majorly achieved using a network through SMS, e-mail, and so on. The presented work suggested a technology of text hiding for protecting secret texts with Unicode characters. The similarities of glyphs provided invisibility and increased the hiding capacity. In conclusion, the proposed method succeeded in securing confidential data and achieving high payload capacity by using the Huffman compression algorithm, which was implemented on an unlimited text length. In addition, this approach has the ability to hide a single bit in every digit or letter in the cover file. Also, the approach meets the cognitive transparency and does not make the modifications apparent on the original data. The method suggested in this work increases the security level through coding a secret message before embedding it within the cover text, with the use of the Advanced Encryption Standard (AES) algorithm.

Based on the current situation, problems and coping measures of network information security in the new era of artificial intelligence and mobile Internet, this paper explores various of network security risks faced by network information, and proposes a new quantum computing reconstruction encryption system based on artificial intelligence, large model and multi-modal fusion application scenarios, as well as network protection technology architecture with the ability to defend against deep fake, which is generated by generative artificial intelligence, and gives the enhancing encryption public key generation algorithm using pseudo-random sequence and verifies the feasibility of this encryption algorithm through encryption and decryption test experiments of different communication information formats, and analyzes the security of the algorithm. The experimental results show that network communication information encryption algorithm based on pseudo-random sequence has high security and encryption efficiency, and can effectively protect the secure transmission of network information.

Image data has been generated massively by devices in medical imaging modalities, cameras, and even by artificial intelligence. Encryption is the powerful method to keep the image content confidential, in which an encryption algorithm must include the confusion and diffusion properties. For massive images, a efficient method of encryption must be chosen to meet the demands of encryption speed and confidentiality. So far, chaos-based image encryption has been an active topic of research because it is considered an effective method to remove the correlation in image data as well as to keep confidential by the involvement of chaotic system in the encryption process. Besides, multiple image encryption algorithms encrypt multiple images in parallel, and it provides highly efficient performance in term of speed if it is implemented on a parallel computing platform such as multiple core processing as well as digital hardware design. Chaos-based multiple image encryption is constructed by integrating a chaotic system into multiple image encryption. Recently, many algorithms of chaos-based multiple image encryption have been proposed, and they are proved to have high efficient in terms of both speed and confidentiality. However, all the existing algorithms of chaos-based multiple image encryption require images of the same size and of the same number of bits representing pixels. Further, they encrypt a cohort of plain images at the same time, and all ciphertext images of a cohort must also be decrypted at the same time. It means that if it does not allow to decrypt one or some selected ciphertext images from a cohort separately; and as a result, it wastes time and energy to decrypt unwanted images. In this paper, three novel structures of chaos-based multiple image encryption are proposed which overcome the drawbacks of existing algorithms. That is, the proposed cryptosystems accept cohort images of different sizes; pixels of images can be represented by different numbers of bits; and any selected ciphertext images from a cohort can be decrypted separately. The security is improved by using the session keys of image-content dependency. The proposed structures of multiple image encryption consist of permutation, substitution, and diffusion processes. The difference between three structures is the order of such processes. A perturbed chaotic map and a linear-feedback shift register are employed to generate pseudo-random bit sequences for session keys. The simulation results for the exemplar designs using the proposed structures show the effectiveness by means of the statistical analysis for the session keys using the NIST randomness test, information entropy, histogram, and correlation coefficients of adjacent pixels in ciphertext images, and security analysis by means of space and sensitivity of the secret key. The hardware implementation on the FPGA platform demonstrates the feasibility of the proposed structures by means of throughput and hardware efficiency.

Aiming at the characteristics of real-time transmission system of mobile terminal voice source, the paper chooses chaos encryption algorithm based on conversion table with better real-time and security. Because of the security problems of Logistic mapping, the improved Logistic mapping is used as pseudo-random number generator (PRNG) of the algorithm, then the method of generating chaotic binary sequences and the encryption algorithm are improved. The results of simulation show that the security and real-time of the algorithm can meet the real-time transmission system of mobile terminal voice source.

Based on the security problem of traditional video encryption algorithm, the compound chaotic map model is used as pseudo-random sequence generator in this paper to generate pseudo-random sequence. A video encryption algorithm based on H.264 standard is designed. First, a new compound chaotic equation is constructed in this paper to generate pseudo-random sequence as the key of this paper. Then, some sensitive data are selected, such as the motion vector difference (MVD), the symbol of MVD and the intra prediction mode. In this paper, the encryption key is analyzed in terms of approximate entropy, information entropy, K entropy and correlation analysis. Experimental results verify that the encryption algorithm has high security.