Based on the stability theory of the linear fractional order system,projective synchronization of a complex network is studied in the paper,and the coupling functions of the connected nodes are identified.With this method,the projective synchronization of the network with different fractional order chaos nodes can be achieved,besides,the number of the nodes does not affect the stability of the whole network.In the numerical simulations,the chaotic fractional order Lu¨ system,Liu system and Coullet system are chosen as examples to show the effectiveness of the scheme.
An image block encryption scheme based on spatiotemporal chaos has been proposed recently.In this paper,we analyse the security weakness of the proposal.The main problem of the original scheme is that the generated keystream remains unchanged for encrypting every image.Based on the flaws,we demonstrate a chosen plaintext attack for revealing the equivalent keys with only 6 pairs of plaintext/ciphertext used.Finally,experimental results show the validity of our attack.
Coupled map lattices (CMLs) are taken as examples to study the synchronization of spatiotemporal chaotic systems.In this paper,we use the nonlinear coupled method to implement the synchronization of two coupled map lattices.Through the appropriate separation of the linear term from the nonlinear term of the spatiotemporal chaotic system,we set the nonlinear term as the coupling function and then we can achieve the synchronization of two coupled map lattices.After that,we implement the secure communication of digital image using this synchronization method.Then,the discrete characteristics of the nonlinear coupling spatiotemporal chaos are applied to the discrete pixel of the digital image.After the synchronization of both the communication parties,the receiver can decrypt the original image.Numerical simulations show the effectiveness and the feasibility of the proposed program.
In this paper,an impulsive synchronisation scheme for a class of fractional-order hyperchaotic systems is proposed.The sufficient conditions of a class of integral-order hyperchaotic systems' impulsive synchronisation are illustrated.Furthermore,we apply the sufficient conditions to a class of fractional-order hyperchaotic systems and well achieve impulsive synchronisation of these fractional-order hyperchaotic systems,thereby extending the applicable scope of impulsive synchronisation.Numerical simulations further demonstrate the feasibility and effectiveness of the proposed scheme.
We propose a novel neural network based on a diagonal recurrent neural network and chaos,and its structure and learning algorithm are designed.The multilayer feedforward neural network,diagonal recurrent neural network,and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map.The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks.
Coupled map lattices are taken as examples to study the synchronisation of spatiotemporal chaotic systems. First, a generalised synchronisation of two coupled map lattices is realised through selecting an appropriate feedback function and appropriate range of feedback parameter. Based on this method we use the phase compression method to extend the range of the parameter. So, we integrate the feedback control method with the phase compression method to implement the generalised synchronisation and obtain an exact range of feedback parameter. This technique is simple to implement in practice. Numerical simulations show the effectiveness and the feasibility of the proposed program.
A digital image encryption scheme using chaotic map lattices has been proposed recently. In this paper, two fatal flaws of the cryptosystem are pointed out. According to these two drawbacks, cryptanalysts could recover the plaintext by applying the chosen plaintext attack. Therefore, the proposed cryptosystem is not secure enough to be used in the image transmission system. Experimental results show the feasibility of the attack. As a result, we make some improvements to the encryption scheme, which can completely resist our chosen plaintext attack.
In this paper, we propose a novel block cryptographic scheme based on a spatiotemporal chaotic system and a chaotic neural network (CNN). The employed CNN comprises a 4-neuron layer called a chaotic neuron layer (CNL), where the spatiotemporal chaotic system participates in generating its weight matrix and other parameters. The spatiotemporal chaotic system used in our scheme is the typical coupled map lattice (CML), which can be easily implemented in parallel by hardware. A 160-bit-long binary sequence is used to generate the initial conditions of the CML. The decryption process is symmetric relative to the encryption process. Theoretical analysis and experimental results prove that the block cryptosystem is secure and practical, and suitable for image encryption.
In this paper, we present the results for the security and the possible attacks on a new symmetric key encryption algorithm based on the ergodicity property of a logistic map. After analysis, we use mathematical induction to prove that the algorithm can be attacked by a chosen plaintext attack successfully and give an example to show how to attack it. According to the cryptanalysis of the original algorithm, we improve the original algorithm, and make a brief cryptanalysis. Compared with the original algorithm, the improved algorithm is able to resist a chosen plaintext attack and retain a considerable number of advantages of the original algorithm such as encryption speed, sensitive dependence on the key, strong anti-attack capability, and so on.
