A robust image encryption algorithm based on Chua's circuit and compressive sensing

A new feedback control of a modified Chua's circuit system

In this paper, the fault detection problem for a class of switched nonlinear systems with unknown functions is solved. First, the unknown internal dynamics are approximated by the radial basis function neural networks due to their powerful approximation capabilities. Then, a switched nonlinear observer is developed. Based on the observer, a fault detection scheme is set up with a switched fault detection threshold instead of a common threshold. At the same time, the boundedness of all the signals in the closed-loop system can be guaranteed by using the average dwell time method. Moreover, the fault detection threshold is dependent on the average dwell time, which implies that the fault sensibility can be improved to a certain extent by selecting the average dwell time. Finally, a simulation example on the Chua's circuit system are employed to show the effectiveness of the proposed scheme.

In this paper we will made a study of the dynamics of Chua's circuit system from the Hamilton-Poisson geometry point of view. Using MAPLE 15 it is analyzed the phase portrait for some specific values of parameters.

Bifurcations and the structure of limit sets are studied for a three-dimensional Chua's circuit system with a cubic nonlinearity. On the base of both computer simulations and theoretical results a model map is proposed which allows one to follow the evolution in the phase space from a simple (Morse-Smale) structure to chaos. It is established that the appearance of a complex, multistructural set of double-scroll type is stimulated by the presence of a heteroclinic orbit of intersection of the unstable manifold of a saddle periodic orbit and unstable manifold of an equilibrium state of saddle-focus type.

The evolution of the target system (leader) in pinning-controlled complex networks may need to be regulated by some control inputs for performing various practical tasks, e.g., obstacle avoidance, tracking highly maneuverable target, and so on. Motivated by this observation, we shall investigate the global pinning synchronization problems for complex switching networks for which the target system is subject to nonzero control inputs. First, using the idea of unit vector function method, a discontinuous coupling law is designed. With the aid of stability theory for switched systems, it is theoretically shown that synchronization in the network under this discontinuous coupling law can be achieved by choosing sufficiently large coupling strengths if the average dwell time (ADT) is bounded below by a positive constant. Second, we use the boundary layer method to design a continuous-coupling law. It has been theoretically shown that the synchronization error is ultimately uniformly bounded (UUB) under this continuous-coupling law. The chattering effect is also avoided in real implementation by using this continuous-coupling law. Furthermore, for networks with unknown external disturbances and unmodeled dynamics, neuro-adaptive-based coupling laws are designed to ensure that the synchronization error of the networks with undirected switching communication topologies under these laws is UUB. The obtained theoretical results are finally validated by performing numerical simulation on coupling Chua's circuit systems.

This study investigates the problem of fault detection (FD) filter design for a class of uncertain Lipschitz systems with time delays, unknown faults, parameter uncertainties and bounded disturbances. A novel FD filter is proposed and the augmented filter system is converted to a linear parameter varying (LPV) system by the reformulated Lipschitz property. Then, two bounded real lemmas (BRLs) are given for the generated residual signal to achieve the fault sensitivity performance in low-/middle-/high-frequency domains and disturbance attenuation performance in the full-frequency domain. Next, the obtained BRLs are further converted into a set of linear matrix inequalities (LMIs) to implement the filter design. Finally, two illustrative simulations including a numerical example and Chua's circuit system clearly demonstrate the advantages of the developed FD scheme.

Understanding synchronization from simple core of chaotic equation

This paper presents a general synchronization technique and an amplitude modulation of chaotic generators. Conventional synchronization and antisynchronization are considered a very narrow subset from the proposed technique where the scale between the output response and the input response can be controlled via control functions and this scale may be either constant (positive, negative) or time dependent. The concept of the proposed technique is based on the nonlinear control theory and Lyapunov stability theory. The nonlinear controller is designed to ensure the stability and convergence of the proposed synchronization scheme. This technique is applied on the synchronization of two identical fractional-order Chua's circuit systems with memristor. Different examples are studied numerically with different system parameters, different orders, and with five alternative cases where the scaling functions are chosen to be positive/negative and constant/dynamic which covers all possible cases from conventional synchronization to the amplitude modulation cases to validate the proposed concept.

A new method of projective synchronization of unidentical chaotic systems is proposed in this letter. This method is based on the stability criterion of linear systems. The response of two unidentical chaotic systems can synchronize up to any desired scaling factor by a suitable separation of the systems. The new method of projective synchronization is suitable not only for the three-dimensional coupled partially linear systems, but also for higher dimensional even hyperchaotic systems. The simplicity and effectiveness of the proposed method are illustrated by the Lorenz system, the four-dimensional partially linear system, the four-dimensional hyperchaotic Rösser system and Chua's circuit system as four numerical examples.

This article investigates the practical fixed-time synchronization of uncertain coupled neural networks via dual-channel event-triggered control. Contrary to some previous studies, the bipartite synchronization of signed graphs representing cooperative and antagonistic interactions is studied. The communication channel is introduced into deception attacks, which are described by Bernoulli's stochastic variables. Based on the concept of two channels, event-triggered mechanisms are designed for sensor-to-controller and controller-to-actuator channels to reduce communication consumption and controller update consumption as much as possible. Lyapunov and comparison theories are used to derive synchronization criteria and explicit expression of settling time. An example of Chua's circuit system is presented to demonstrate the feasibility of the obtained theoretical results.

The methods of nonconstant feedback impulse control of chaos are introduced. The approach is based on the similarity of the return maps of dissipative continuous-time systems with one dimensional maps. The methods are illustrated for the Chua's circuit (1992), Rossler oscillator, and phase-locked loop system.

Soil salinization is very complex and its evolution is affected by numerous interacting factors produce strong non-linear characteristics. This is the first time fractional order chaos theory has been applied to soil salinization-level classification to decrease uncertainty in salinization assessment, solve fuzzy problems, and analyze the spectrum chaotic features in soil with different levels of salinization. In this study, typical saline soil spectrum data from different human interference areas in Fukang City (Xinjiang) and salt index test data from an indoor chemical analysis laboratory are used as the base information source. First, we explored the correlation between the spectrum reflectance features of soil with different levels of salinization and chaotic dynamic error and chaotic attractor. We discovered that the chaotic status error in the 0.6 order has the greatest change. The 0.6 order chaotic attractors are used to establish the extension matter-element model. The determination equation is built according to the correspondence between section domain and classic domain range to salinization level. Finally, the salt content from the chemical analysis is substituted into the discriminant equation in the extension matter-element model. Analysis found that the accuracy of the discriminant equation is higher. For areas with no human interference, the extension classification can successfully identify nine out of 10 prediction data, which is a 90% identification accuracy rate. For areas with human interference, the extension classification can successfully identify 10 out of 10 prediction data, which is a success rate of 100%. The innovation in this study is the building of a smart classification model that uses a fractional order chaotic system to inversely calculate soil salinization level. This model can accurately classify salinization level and its predictive results can be used to rapidly calculate the temporal and spatial distribution of salinization in arid area/desert soil.

In resource-constrained communication environments, important image data needs to be compressed before encrypted transmission. This paper proposes effective solutions to this issue. Firstly, a new one-dimensional discrete chaotic system model was constructed based on the logistic system and fractional structure. Through theoretical analysis combined with numerical simulation experiments, it has been proven that the proposed new system has excellent chaotic characteristics. Compared with some traditional one-dimensional chaotic systems, the new system has a wider range of chaotic parameters and stronger complexity, making it more suitable for image data encryption. Secondly, a high-compression-ratio image compression method based on improved lifting wavelet transform and a fast image encryption algorithm based on the new chaotic map are proposed. Simulation experiments and security analysis results show that the proposed image compression–encryption scheme has excellent performance and less time overhead. It has good resistance to various cryptanalysis attacks and strong robustness to noise and data loss attacks, which indicates that the proposed image compression–encryption scheme has good application potential in resource-constrained communication environments. The main contribution of this article is the design of a new chaotic system model with practical performance and the development of a new application case. The main novelty of this paper is the proposal of a fast algorithm for high compression ratio and encryption of images.

In recent years, with the development of the image processing technology, the protection to the authenticity and integrity of digital images has always been a topic of great concern. A blind image authentication technology with high tamper detection accuracy under different common attacks is urgently needed. In this paper, an improved fragile watermarking based on local binary pattern (LBP) for blind tamper detection in images is proposed. In this method, the binary watermark is generated by LBP operator, which is often used in texture analysis and pattern recognition. In order to improve the security of the proposed method, Arnold transform and logistic map are used to scramble the watermark. Then the watermark is inserted into the least significant bit (LSB) of original pixels. Since the watermark is constructed from the image itself, no original image is needed in tamper detection. The LBP map of watermarked image is compared with the extracted watermark to determine whether it is tampered or not. Compared with other state-of-the-art algorithms, experimental results show that the proposed scheme achieves good performance in tamper detection and localization under various attacks.

Compressive Sensing (CS) is a new sampling theory which allows signals to be sampled at sub-Nyquist rate without loss of information. Fundamentally, its procedure can be modeled as a linear projection on one specific sensing matrix, which, in order to guarantee the information conservation, satisfies Restricted Isometry Property (RIP). Ordinarily, this matrix is constructed by the Gaussian random matrix or Bernoulli random matrix. In previous work, we have proved that the typical chaotic sequence - logistic map can be adopted to generate the sensing matrix for CS. In this paper, we show that Toeplitz-structured matrix constructed by chaotic sequence is sufficient to satisfy RIP with high probability. With the Toeplitz-structured Chaotic Sensing Matrix (TsCSM), we can easily build a filter with small number of taps. Meanwhile, we implement the TsCSM in compressive sensing of images.