Pseudo-random Sequence Generator Research Articles

A Novel Parameter-Variabled and Coupled Chaotic System and Its Application in Image Encryption with Plaintext-Related Key Concealment.

The design of a chaotic system and pseudo-random sequence generation method with excellent performance and its application in image encryption have always been attractive and challenging research fields. In this paper, a new model of parameter-variabled coupled chaotic system (PVCCS) is established by interaction coupling between parameters and states of multiple low-dimensional chaotic systems, and a new way to construct more complex hyperchaotic systems from simple low-dimensional systems is obtained. At the same time, based on this model and dynamical DNA codings and operations, a new pseudo-random sequence generation method (PSGM-3DPVCCS/DNA) is proposed, and it is verified that the generated pseudo-random sequence of PSGM-3DPVCCS/DNA has excellent random characteristics. Furthermore, this paper designs a novel pixel chain diffusion image encryption algorithm based on the proposed parameter-variabled coupled chaotic system (PVCCS) in which the hash value of plaintext image is associated with the initial key to participate in the encryption process so that the encryption key is closely associated with plaintext, which improves the security of the algorithm and effectively resists the differential cryptanalysis risk. In addition, an information hiding method is designed to hide the hash value of plaintext image in ciphertext image so that the hash value does not need to be transmitted in each encryption, and the initial key can be reused, which solves the key management problem in application and improves the application efficiency of the encryption algorithm. The experimental analysis shows that the chaotic system constructed in this paper is creative and universal and has more excellent chaotic characteristics than the original low-dimensional system. The sequence generated by the pseudo-random sequence generation method has excellent pseudo-random characteristics and security, and the image encryption algorithm can effectively resist differential cryptanalysis risk, showing advanced encryption performance.

FOR PSEUDORANDOM SEQUENCES BASED ON ELLIPTIC CURVE ISOGENIES GENERATING METHOD

The pseudorandom sequences generation is a cryptographic systems fundamental aspect that affects cryptographic strength. One of these sequences advanced generating methods involves the use of elliptic curves (ECs), in particular by exploiting the isogeny properties of ECs. This approach not only improves the security features of cryptographic algorithms, but also ensures efficiency and reliability in the generation process. The use of isogenic transformations - morphisms between elliptic curves that preserve their group structure - further enriches the technique by introducing complex algebraic operations that are difficult to solve. Recent research has detailed the effectiveness of pseudorandom sequence generators based on elliptic curves. Methods have been developed that exploit the properties of elliptic curves over finite fields to generate sequences with low correlation and high linear complexity. There is also another approach that uses linear shift feedback registers (LFSRs) in combination with elliptic curve points to generate pseudorandom sequences. The new obtained method makes it possible to increase the number of internal states of the Dual_EC_DRBG generator by √n times, where n is the number of cyclic subgroups of simple order of the initial curve. This increases the complexity of disclosing the law of formation of the DRBG by an attacker. The application of the developed method also allows to avoid the existing disadvantages of Dual_EC_DRBG The article investigates the use of EC isogenies in the generation of pseudorandom sequences, considering their potential for improving cryptographic strength. By means of a detailed analysis of the algebraic structure and properties of these transformations, a method for PSPs generating is developed that can potentially provide advantages over existing methods in terms of security and efficiency in the transition period to post-quantum cryptography.

STATISTICAL PROPERTIES OF THE PSEUDORANDOM SEQUENCE GENERATION ALGORITHM

One of the most important issues in the design of cryptographic algorithms is studying their cryptographic strength. Among the factors determining the reliability of cryptographic algorithms, a good pseudorandom sequence generator, which is used for key generation, holds particular significance. The main goal of this work is to verify the normal distribution of pseudorandom sequences obtained using the generation algorithm and demonstrate that there is no mutual statistical correlation between the values of the resulting sequence. If these requirements are met, we will consider such a generator reliable. This article describes the pseudorandom sequence generation algorithm and outlines the steps for each operation involved in this algorithm. To verify the properties of the pseudorandom sequence generated by the proposed algorithm, it was programmatically implemented in the Microsoft Visual C++ integrated development environment. To assess the statistical security of the pseudorandom sequence generation algorithm, 1000 files with a block length of 10000 bits and an initial data length of 256 bits were selected. Statistical analysis was conducted using tests by D. Knuth and NIST. As shown in the works of researchers, the pseudorandom sequence generation algorithm, verified by these tests, can be considered among the reliable algorithms. The results of each graphical test by D. Knuth are presented separately. The graphical tests were evaluated using values obtained from each test, while the chi-squared criterion with degrees of freedom was used to analyze the evaluation tests. The success or failure of the test was determined using a program developed by the Information Security Laboratory. Analysis of the data from the D. Knuth tests showed good results. In the NIST tests, the P-value for the selected sequence was calculated, and corresponding evaluations were made. The output data obtained from the NIST tests also showed very good results. The proposed pseudorandom sequence generation algorithm allows generating and selecting a high-quality pseudorandom sequence of a specified length for use in the field of information security.

Enhancing Financial Security: Chaotic Map Integration with Biometric Data

"As a digitalization of attendance systems and identity authentication systems at places like factories, airports, educational institutions, healthcare centers, etc. They contain a lot of biometric data like fingerprints, so there is a high risk of data breaches from the databases used by the authentication centers. The biometrics are less costly to upkeep, so it is very economical. The biometric data is susceptible, and sometimes attackers may use it to cause financial damage using these biometric data, as they are used in many government identity cards as proof. Due to this, it becomes essential to protect these data. Research communities have proposed many image security solutions to prevent security breaches. Unfortunately, many cryptosystems today have excessive computational complexity and inadequate security. Thus, protecting these biometric image data and lowering computing complexity are the primary goals of our work. So we have proposed an encryption technique which contain dual confusion followed by a diffusion process. For the first part of confusion, we have designed a divide-rotate algorithm and for the second phase, we have developed a pixel shifting algorithm. A pseudo-random sequence generator is used to generate a chaotic range of values and diffuse the image, and in this process, a Logistic map is used. Studies on security and performance show that the suggested approach has a high degree of randomness and is resistant to statistical entropy-based, differential as well as brute-force attacks. From the analysis and findings, it is clear that the suggested method is incredibly sensitive, financially trustworthy, and performs better than other similar state-of-the-art systems, all with reduced computing complexity."

The hyperbolic sine chaotification model and its applications

Some existing chaotic systems suffer from issues such as period windows, discontinuous parameter ranges, and dynamical degradation, which seriously limit their application. Therefore, designing high-performance anti-degradation chaotic systems is of great significance. In this paper, a novel hyperbolic sine chaotification model (HSCM) is proposed. It allows for the use of any chaotic maps or linear functions as the seed maps, and employs a closed-loop modulation coupling (CMC) method to extend it to high-dimensional (HD) chaotic maps. Theoretical and experimental results show that this model can effectively improve the Lyapunov exponent (LE) of the seed chaotic map and expand the parameter ranges. In addition, it can also resist the dynamical degradation under finite computational precision. Based on the HSCM, a novel eight-dimensional (8D) HSCM is designed, and implemented through field-programmable gate array (FPGA) in both serial and parallel modes, respectively. Furthermore, the novel chaotic maps are applied to pseudo-random sequence generator (PRNG) and image compression under finite computing precision. Experimental results indicate that the novel chaotification model has greatly broad application prospects.

Justification of methods for calculating and analyzing the properties of pseudorandom and random sequences based on DNA

An integral requirement for modern information systems is to provide users with services such as confidentiality, integrity, availability, and irrefutability. The quality of such services directly depends on cryptographic transformations, an important component of most of which is randomness. Therefore, the generation of pseudorandom and random sequences is one of the most relevant and important tasks in cryptography. Such sequences are generated based on physical and non-physical noise sources. Our previous studies indicate the theoretical possibility to use DNA as a noise source and, accordingly, as a source of random sequences. Any noise source "contains randomness", i.e. it has a certain amount of entropy, but a sample from such a source will not always have good properties. That is why there is a need for tools that can obtain sequences with good randomness properties of samples from the DS sequences with good randomness properties of samples from the noise source (by, for example, some kind of enhancement). Such sequences should satisfy the necessary conditions: be statistically indistinguishable, uniform, etc. NIST-approved DRBG designs can be used to guarantee this. Such constructions are most often based on strong crypto-primitives, such as hashes, HMACs, or block or stream ciphers in the required modes. This work is devoted to newly developed methods for obtaining pseudorandom and random sequences based on DNA sequences using the national standard for block symmetric encryption DSTU 7624:2014 in the counter (CTR) operation mode, as well as methods for comparing sequences (both DNA and binary). The work essentially opens the topic of obtaining random sequences based on DNA, since previous studies of DNA in cryptography have focused on the use of DNA in encryption and steganography. The paper presents the results of solving such issues as the development of methods for obtaining DNA-based sequences, the evaluation of statistical and stochastic properties of such sequences, and the evaluation of similarity based on k-mer and MinHash distances. The results obtained indicate the prospects and relevance of further research in this area.

Temporal action segmentation for video encryption

Videos contain temporal information, enabling them to capture the dynamic changes of actions and provide richer visual effects. Traditional video encryption methods involve decomposing videos into frames and encrypting them frame by frame, which results in significant resource consumption. This paper proposes a video encryption method based on temporal action segmentation. This methodology involves the identification and extraction of pivotal frames from a video dataset, followed by the encryption of these significant key frames. This approach serves to enhance the efficacy of the video encryption algorithm. The method consists of three modules. The first module uses temporal action segmentation to classify video frames and extract important frames for the second module’s input. The second module encrypts the extracted key frames using a chaos-based encryption algorithm, thereby reducing the time cost of video encryption. The third module outputs the encrypted video. During the encryption process, a large amount of key stream is required. To address this, the paper introduces a new pseudo-random sequence generation method called two-dimensional Gramacy&Lee map (2D-GLM). Comprehensive comparative analysis clearly demonstrates that compared to other systems, 2D-GLM exhibits superior performance and can generate a large number of high-performance pseudo-random sequences. The proposed algorithm is tested on GTEA, and the simulation results demonstrate that it can accomplish video encryption tasks with high security.

3D medical image encryption algorithm using biometric key and cubic S-box

Considering the scarcity of research on 3D medical image encryption, this paper proposes a novel 3D medical image encryption scheme based on biometric key and cubic S-box. To enhance the data security, biometric keys are utilized to overcome the limitations of traditional methods where secret keys with no practical meaning, fixed length, and finite key space, while cubic S-box is constructed to increase the nonlinearity of image cryptosystem. The proposed cryptosystem mainly consists of four phases: pseudo-random sequence generation, confusion, substitution, and diffusion. Firstly, the stepwise iterative algorithm based on coupled chaotic systems is utilized for generating pseudo-random sequences for confusion and diffusion. Secondly, the confusion algorithm based on multiple sorting can scramble pixel positions in 3D images. Thirdly, guided by the designed cubic S-box, pixel substitution is executed sequentially. Lastly, the diffusion algorithm based on ECA and finite field multiplication is capable of increasing the plaintext sensitivity of cryptosystem by concealing the statistical characteristics of plaintext. Simulation experiments performed on multiple 3D medical images demonstrate that the proposed encryption scheme exhibits favorable statistical performance, sufficiently large key space, strong system sensitivity and robustness, and can resist various typical cryptographic attacks.

Enhancing FPGA Testing Efficiency: A PRBS-Based Approach for DSP Slices and Multipliers

The multiplication operations are pivotal in (Application-Specific Integrated Circuits) ASICs and Digital Signal Processors (DSPs). The integration of Field-Programmable Gate Arrays (FPGAs) into modern embedded systems, efficient Built-in Self-Tests (BISTs), particularly for complex components like DSP slices, is essential. This paper evaluates Pseudo Random Binary Sequence (PRBS) generators and checkers as BIST tools for high-speed data transfers in FPGAs. The design achieves minimal errors and remarkable efficiency with less than 4% logic utilization within available Look-Up Tables (LUTs). The testing of embedded multipliers in modern FPGAs is analyzed, shedding light on their performance. The analysis includes Built-in Self-Test (BIST), PRBS generator, PRBS checker, and Bit Error Rate (BER), providing insights into FPGA-based testing. This analysis assesses PRBS tools for high-speed FPGA data transfers. A hybrid multiplier design, featuring BIST and PRBS capabilities, notably reduces DSP slice utilization from 16% to 5%. This liberated FPGA resource enhances operational capabilities. The runtime PRBS data control at the block level design exemplifies adaptability in FPGA testing. The findings underscore PRBS-based BIST potential in FPGA testing. The hybrid multiplier not only optimizes FPGA resources but also aligns with dynamic digital system requirements. This research aids FPGA designers and engineers in advanced testing strategies for evolving embedded systems.

Design of Pseudo-random Sequence Generator based on Three-dimensional Discrete Chaotic System

In this paper, a pseudo-random sequence generator with better randomness is constructed through the targeted improvement of chaotic system. Firstly, a new three-dimensional discrete chaotic system is proposed on the basis of the existing one-dimensional logistic chaotic system by improving and optimizing the dimensionality and coupling mode, and its Lyapunov exponent and other characteristics are analyzed; then, based on the chaotic system, a pseudo-random sequence generator is designed by using post-processing and heterodyne, etc.; after that, the performance of the pseudo-random sequence is discussed by using the evaluation methods of relevance, homogeneity, and NIST test. After that, the performance of the pseudo-random sequence is discussed using correlation, uniformity, NIST test and other evaluation methods. The results show that the three-dimensional discrete chaotic system has good chaotic properties, and the pseudo-random sequence generator based on this three-dimensional discrete chaotic system has good random performance and can pass the NIST test. The work in this paper provides an idea for the improvement of logistic mapping chaotic system and enriches the application form of pseudorandom sequence generator in information security.

Signature functional control of digital automatic device register operations

The development of digital operating automatic devices models of the systems with the property of high functional controllability of hardware and software tools for the performance of computational functions (operations) on a real scale becomes a priority task in the context of ensuring high efficiency and reliability of monitoring the functioning of digital metrological telemetric measurement and control systems of critical infrastructure problem growing relevance. In the article, based on a critical analysis of known methods for digital systems functional control, a method of ensuring the operational controllability of digital automatic devices is proposed based on the concept implementation of predicting (forecasting) control signatures of tuples and their state. Relevant concepts are introduced, and a structural-functional model of functional control for digital automatic device with «hard» logic based on the method of signature prediction is proposed. In the context of the practical implementation of the proposed method of predicting signatures on each operating cycle of the digital automatic device, a system of control signature equations formulas (signature functional control rules) is given for the basic types of digital automatic device register operations with «hard» logic. This makes it possible to implement a new functional control principle (signature functional control by the method of signature prediction) of digital automatic devices by introducing a unified hardware redundancy (synthesized hardware node of a signature functional control) from functionally complete elementary combinational structures from a finite set (standard set). In this regard, the relevance of functional control by the method of predicting signatures for generators of pseudorandom sequences of the maximum length in the digital automatic device of cryptographic encryption by jamming measurement information during its transmission in telecommunication channels of management systems of critical infrastructure objects in the conditions of possible cyberattacks is reasonably grounded. The scientific novelty of the obtained theoretical results is the authors' proof of the need to develop further the methodology of functional control of a general-purpose digital automatic device and, in particular, of telemetric measurement and control systems of critical infrastructure based on the use of the author's mathematical apparatus of synthesis «signature Boolean-polynomial algebra».

Evaluation of the parameters of the simulation model of microcontroller authenticators

Microcontroller technologies are the basis for intelligent devices, so cybersecurity issues are important when ensuring the exchange of information between them. As these devices form a variety of intelligent systems, authentication becomes a key aspect of cybersecurity. This process distinguishes between legitimate and illegitimate devices, allowing legitimate devices to access system resources and reject requests from illegitimate ones. Today there is a problem of choosing an authentication factor for a large number of electronic devices of the same type in the information system. The purpose of this study is to find out the possibility of a programmatic approach to simulating a "biometric" authentication template. To solve the goal, it is necessary to implement a simulator of templates with the properties of biometrics in a programming language, to evaluate the distribution of distances between pairs of templates, and to evaluate the parameters of the generated sequences from the point of view of brute force probability. In this study, a solution to the problem is proposed, which combines the ideas of the biometric factor and the possibilities of fast software generation of authenticators for microcontrollers. The work is devoted to the evaluation of the model parameters of the simulator of dynamic bit patterns of authentication based on the generator of pseudo-random impulse Poisson sequences. The work highlights the basic principles of the simulator's functioning and the advantages of using dynamic templates to ensure cyber security of electronic devices built on the basis of microcontrollers. Estimates of the main parameters of the simulator model were performed. The results of the work are important for the development of security of electronic systems and means of authentication in the context of cybersecurity of microcontrollers.

Quantum-Secure Hybrid Blockchain System for DID-Based Verifiable Random Function with NTRU Linkable Ring Signature

In this study, we present a secure smart contract-based Verifiable Random Function (VRF) model, addressing the shortcomings of existing systems. As quantum computing emerges, conventional public key cryptography faces potential vulnerabilities. To enhance our VRF’s robustness, we employ post-quantum Ring-LWE encryption for generating pseudorandom sequences and a NTRU lattice-based linkable ring signature scheme. Given the computational intensity of this approach and associated on-chain gas costs, we propose a hybrid architecture of VRF system where both on-chain and off-chain can communicate in a scalable and secure way. Our decentralized VRF employs multi-party computation (MPC) with blockchain-based decentralized identifiers (DID), ensuring the collective efforts of enhanced randomness and security. We show the security and privacy advantages of our proposed VRF model with the approximated estimation of overall temporal and spatial complexities. We also evaluate our VRF MPC model’s entropy and outline its Solidity smart contract integration. This research also provides a method to produce and verify the VRF output’s proof, optimal for scenarios necessitating randomness and validation. Lastly, using NIST SP800-22 test suite for randomness, we demonstrate the commendable result with a 97.73% overall pass rate on 11 standard tests and 0.5459 of average 𝑝-value for the total 176 tests.

SOFTWARE GENERATORS IN THE GPSS WORLD ENVIRONMENT FOR DISTRIBUTIONS-PROBABILITY MIXTURES WITH QUALITYASSESSMENT RESULTS

This article presents quality assessment results for the software generators of pseudo-random sequences (PRS) presented in [1; 2] for QS simulation, including second-order hyper-Erlang and hyper-exponential distributions of the second order, that flows organically from these works. These distribution laws are in demand in queuing theory as it provides a big range of changes in the variation coefficient which plays an important role in the average queue delay calculating. There is no data on such generators neither in scientific literature, no in the GPSS WORLD library. Software generator quality evaluation, regardless of the programming language, is usually made according to statistical tests. In this case, chi-squared and Kolmogorov-Smirnov’s tests are used. In addition, the comparison between theoretical and statistical aspects of the corresponding order is provided. Unlike simple distribution laws, for which the use of the above mentioned statistical tests is provided for in well-known software products and does not cause any difficulties, in our case automatic testing is impossible. The well-known packages STATISTICA, STATGAPHICS, Matlab/Simulink, etc. do not provide for the use of the hyper-Erlang and hyper-exponential distribution laws we consider. Therefore, the Pearson statistical test is calculated and checked manually. The presented results should be useful for professionals of discrete event modeling in the GPSS WORLD environment.

A RGB image encryption technique using chaotic maps of fractional variable-order based on DNA encoding

This paper presents a controller-based synchronization scheme in a leader-follower architecture for chaotic maps of fractional variable-order. The proposed scheme demonstrates successful synchronization of three different chaotic maps through simulation results. The implementation on Arduino UNO boards is used to showcase the relatively low algorithm complexity of the proposed scheme. Additionally, the paper explores a potential application of the proposed scheme in an RGB image encryption system, leveraging the chaotic behavior of the system for pseudo-random sequence generation. The encoding scheme utilizes the complementary property of Deoxyribonucleic acid (DNA) molecule bases. The presented encryption scheme employs the variable-order of the fractional derivative as a key for improved safety. This enhancement improves the methodology resistance against brute-force attacks while maintaining resilience against other cryptoanalysis techniques.

Оценка точности цифровой обработки сильно зашумленных сигналов с помощью эвристических алгоритмов

Heuristic algorithms are often used as an alternative when solving problems of high computational complexity or lacking an exact solution, allowing to quickly obtain the desired result. Usually, they do not have a strict mathematical justification, but their application is justified in terms of practicality. Formally, algorithms that use approximate methods can be classified as heuristic. However, when applying them, the problem of determinism lack is often arises, which does not always allow one to evaluate the solution obtained accuracy. The paper considers a methodical approach to assessing the accuracy of heuristic algorithms designed to determine the useful signal shape and parameters on the strong noise component background. It is based on the method of analogy and consists in modeling an artificial signal with given parameters and a background noise interference similar in its characteristics to additive white Gaussian noise. In this case, the noise component is formed by software using a pseudo-random number sequence generator. Such generators are included in the packages of almost all high-level programming languages built-in functions. A comparative analysis of the real and artificial noise characteristics is presented, that shown the problem solving by numerical modeling possibility. The results of accuracy estimation in determining the artificial signal parameters, that is separated from the noise component using piecewise linear approximation and averaging heuristic algorithms, are obtained. The problem of empirical data smoothing with the discrete signal equivalent replacement by a quadratic functions whose parameters provide a piecewise parabolic approximation its shape is also considered. This procedure eliminates the residual signal bounce that inevitably occurs as a result of linearization and allows further recording at any sampling rate. Thus, the proposed approach allows us to quantify the accuracy of heuristic algorithms used in determining the expected signal parameters.

SIMULATION MODEL OF A QS WITH HYPEREXPONENTIAL DISTRIBUTION IN THE GPSS WORLD ENVIRONMENT

This article presents results obtained on the development of a pseudo-random sequence generator for simulation modeling of queueing system (QS) with second-order hyperexponential input distribution. In the scientific literature on GPSS WORLD, including web resources, the authors did not find any data in this subject area. The GPSS WORLD library includes many generators of various distribution laws, but there are no generators for such important composite distributions according to the queuing theory. It is known that the hyperexponential distribution concept provides a wide range of changes in the random variable variation coefficient from unity to an arbitrarily large value. Due to the fact that the variation coefficients of arrival and service intervals play an important role in estimating the delay of queue claims in queuing systems, thus this distribution concept plays a special role in modeling of QS. For a hyperexponential distribution of the second order, the authors previously obtained numerical-analytical results based on the Lindley integral equation spectral solution method. The article describes a developed algorythm and a program on GPSS WORLD to simulate the functioning of QS with hyperexponential input distribution incl. description of operation of logical switches. The difference between analytical and simulation modeling of the two-phase representation of a given distribution concept is explained on the example of the developed model. The adequacy of the obtained results was confirmed by comparing the simulation results with the results of numerical simulation in the Mathcad environment.

Hidden dynamics of memristor-coupled neurons with multi-stability and multi-transient hyperchaotic behavior

The coupling of memristors has been extensively studied in continuous neural models. However, little attention has been given to this aspect in discrete neural models. This paper introduces a Discrete Memristor-Coupled Rulkov Neuron (DMCRN) map, utilizing discrete memristors to estimate synaptic functionality. The proposed model is subjected to theoretical analysis, revealing hidden behaviors within the map. Through numerical methods, the rich and complex dynamical behaviors of the DMCRN map are studied, including hyperchaos, hidden attractors, multi-stability and multi-transient, as well as the firing patterns. Additionally, a simple pseudo-random sequence generator (PRNG) is designed based on the generated hyperchaotic sequences, providing a reference for further applications of DMCRN map. In addition, a digital experiment is implemented on a DSP platform, realizing the DMCRN map and obtaining hyperchaos. Both experimental and numerical results demonstrate that the coupling of discrete memristors allows for the estimation of synaptic connections in neurons, resulting in a more complex and interesting discrete neuron model.

A Class of Discrete Memristor Chaotic Maps Based on the Internal Perturbation

Further exploration into the influence of a memristor on the behavior of chaotic systems deserves attention. When constructing memristor chaotic systems, it is commonly believed that increasing the number of memristors will lead to better system performance. This paper proposes a class of chaotic maps with different discrete memristors, achieved through internal perturbation based on the Sine map. The I-V curve of the discrete memristor has a symmetrical structure. The dynamic characteristics of the designed system are analyzed using the chaotic attractor phase diagram, Lyapunov exponent (LE) spectrum, and bifurcation diagram. Numerical simulations demonstrate that internal perturbations of discrete memristors enhance the Sine map’s chaotic characteristics, expand the chaos range, and improve the ergodicity and LE value. Moreover, the type of discrete memristors has a significant impact on the dynamic characteristics of the system, while the number of discrete memristors has little influence. Therefore, in this paper, a direction for the design of a discrete memristor chaotic system is provided. Finally, a discrete memristor chaotic map with a simple structure and better performance is selected. Based on this, a pseudo-random sequence generator is designed, and the generated sequence passes the National Institute of Standards and Technology (NIST) test.

A novel lorenz-sine coupling chaotic system and its application on color image encryption

The chaos-based image encryption has been extensively studied for image security owing to its high efficiency. However, both the complexity of the chaotic system and the chaos-based image encryption method must be enhanced. A Lorenz-Sine coupling chaotic system with complex behavior and a novel image encryption scheme is presented in this work. By adding a nonlinear controller containing sinusoidal function to the Lorenz system, we obtain smooth chaotic attractors with a unique appearance. Analysis of the dynamical properties shows that it has a multi-symmetry stranger attractor and a large chaotic range. Based on the proposed chaotic system, a pseudorandom sequence generator is designed to generate keys with high randomness. Furthermore, an image encryption scheme using spiral-rotation and random permutation is presented. Cipher-feedback is employed to increase the avalanche effect. The encryption efficiency and the security analysis are simulated. The result shows that the correlation coefficient between the adjacent pixels of the proposed scheme achieves The NPCR of the proposed scheme is larger than 0.9661 and the UACI falls within the theoretical value of UACI with a significance level of 0.05. Thus, the proposed scheme is more capable against differential attacks. Furthermore, it is more robust against noise attacks and cropping attacks.