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Cryptanalysis of key expansion algorithms in AES and SM4 revealed that (1) there exists weaknesses in their S-Boxes, and (2) the round key expansion algorithm is reversible, i.e. the initial key can be recovered from any round key, which may be explored by the attacker. To solve these problems, first we constructed a nondegenerate 2D exponential hyper chaotic map (2D-EQCM), derived a recursion formula to calculate the number of S-Boxes, and designed a strong S-Box construction algorithm without such weakness. Then based on 2D-EQCM and S-Box, we designed an irreversible parallel key expansion algorithm, which could transform the initial key to any number of relatively independent round keys. Security and statistical analysis demonstrated the flexibility and effectiveness of the proposed irreversible parallel key expansion algorithm.

In this paper, the exponential stability of a stochastic delay system with impulsive signal is considered, and stability theorem of this system is proposed based on the Lyapunov–Razumikhin method; the convergence rate is also given, which gives theoretical foundation to chaos control and synchronization using the impulsive method. Finally, the classic delay chaos system with white noise and impulsive signal is employed to verify the feasibility and effectiveness of our theorem.

This paper investigates the anticontrol of the fractional-order chaotic system. The necessary condition of the anticontrol of the fractional-order chaotic system is proposed, and based on this necessary condition, a 3D fractional-order chaotic system is driven to two new 4D fractional-order hyperchaotic systems, respectively, without changing the parameters and fractional order. Hyperchaotic properties of these new fractional dynamic systems are confirmed by Lyapunov exponents and bifurcation diagrams. Furthermore, a color image encryption algorithm is designed based on these fractional hyperchaotic systems. The effectiveness of their application in image encryption is verified.

Contrary information is recorded in the process of Ribonucleic Acid transcription, which is similar to the anti-synchronization process. In this paper, the anti-synchronization of coupled Boolean networks is investigated. Firstly, the definition of anti-synchronization is introduced, and the drive-response Boolean networks dynamics are translated into linear representations with the semi-tensor product. Then, a necessary and sufficient condition is obtained for anti-synchronization of coupled Boolean networks. Finally, simulation example is presented to further illustrate the efficiency of the proposed method.

By analyzing the disadvantages of the traditional KNN using lazy learning that directly classify the data based on the K neighboring classes using the majority voting method, a new Sigmoid weighted classification algorithm WKS (Weighted KNN Based On Sigmoid) was proposed. WKS provides a new method for learning and training, since each training data d i ∊ D contributes to the correct classification of the classifier-expressed by weight W i . WKS combined with the idea of AdaBoost algorithm that change the data weight distribution in the training base classifier, using Sigmoid function to achieve the weight update, the neighbors with correct contribution to the classify increasing the sample weight, otherwise decrease the weight. Firstly, The training set was modeled by training, and then use the testing set to do classification. By UCI data sets experiment, the experimental results show that WKS has better classification accuracy than traditional KNN algorithm.

As an effective method in dealing with the massive data, the serial processing, aiming to obtain the useful information quickly, cannot satisfy our calculation requirements with high-performance. However, both distributed computing and parallel computing are good choices in calculating high-volume data with high-performance. As a parallel computing framework based on memory computing large data, Spark was of great concern as soon as it was proposed. This paper, based on the limitations of k-medoids algorithm which is sensitive to the center point and requires a large number of iterations in the process of calculating the new center point, puts forward a parallel algorithm named Canopy-Kmedoids within the platform of Spark. The algorithm obtains the K center points by the Canopy algorithm. By analyzing the performance of parallel operators and the advantage of using Spark to have good performance for iterative computation. In addition, this method reduces the frequency of reading or writing the shuffle and disk, which effectively overcomes the shortcomings of k-medoids. The experimental results show that the parallel algorithm achieves a relative ideal speedup ratio and can handle the massive data efficiently as well.

A chaos-based color image encryption scheme using bijection is designed. The whole image is diffused by exclusive or (XOR) operation for random rounds, each color component is separated into blocks with the same size. A bijective function f : B → S between block set B and S-box set S , is built. The corresponding 8 × 8 S-box is dynamically generated by the Chen system with variable conditions. The ciphered image can be obtained after substituting each block with the paired S-box. Numerical simulation and security analysis demonstrate that the scheme is practical in image encryption.

In this paper, the stochastic asymptotical stability of stochastic impulsive differential equations is studied, and a comparison theory about the stochastic asymptotical stability of trivial solution is established. From the comparison theory, we can find out whether the stochastic impulsive differential system is stochastic asymptotically stable by studying the stability of a deterministic comparison system. As an application of this theory, we study the problem of chaos synchronization in Chua circuit using impulsive method. Finally, numerical simulation is employed to verify the feasibility of our method.

Recently, Tseng et al. proposed a novel key agreement protocol based on chaotic maps. They claimed that the protocol achieved session key agreement between a server and a user, and allowed the user to anonymously interact with the server. This paper, however, will demonstrate that Tseng et al.’s protocol can not guarantee user anonymity and protocol security against an insider adversary who is a legal user, and it can not provide perfect forward secrecy. Furthermore, the current paper presents a new key agreement protocol based on Chebyshev chaotic map in order to conquer these problems. In contrast with Tseng et al.’s protocol, the proposed protocol is more secure and preserves user anonymity.

The concept of module-phase synchronization was proposed. The chaos synchronization between drive system and response system was achieved in module space and phase space respectively (module-phase synchronization). Different from the evolutions in real space, there is no pseudorandom behavior in phase space when module-phase synchronization achieve. All the phases of complex state variables switched between two fixed values which are determined by initial values of drive system. And the modules varied within a bounded field. The theoretical analysis and the simulations were also given.

The exponential p-moment stability of stochastic impulsive differential equations is addressed. A new theorem to ensure the p-moment stability is established for the trivial solution of the stochastic impulsive differential system. As an application of the theorem proposed, the problem of controlling chaos of Lorenz system which is excited by parameter white-noise excitation is considered using impulsive control method. Finally, numerical simulation results are given to verify the feasibility of our approach.

Improving arousal recognition accuracy by using EEG signals is important for emotion recognition. In this research, discrete wavelet transform is used to extract features, and a cross-level method is adopted to select effective features. The cross-level method shows great potential for two-level arousal classification, and the recognition accuracy reaches 91.8%. The sensitivity of EEG channels is also discussed based on two ranking methods of SCP (single-channel performance) and ANOVA (analysis of variance). Finally, arousal recognition method based on EEG signals is applied to construct a Japanese emotion database.

We consider the sensor deployment problem in the context of distance uncertainty. It is characterized by differentiated arrangement of specific detection probability thresholds at different locations. The problem is formulated as an integer linear programming (ILP) model firstly, aiming at optimizing the number of sensors and their locations. Based on the robust discrete optimization methodology, the uncertain model is transformed into an equivalent ILP problem considering distance uncertainty. The proposed approach can control the tradeoff between optimality and robustness by varying the parameters named protection levels. Uniform and non-uniform event detection probabiliy distributions are considered in the experiment. The results show that, as the distance uncertainty increases, the constraint violation can be avoided in the robust model and the robust solution can provide a significant improvement at the expense of a small loss in optimality when compared to the optimal solution of a deterministic scenario.

A high precision fast projective synchronization method for chaotic systems with unknown parameters was proposed by introducing optimal matrix. Numerical simulations indicate that the precision be improved about three orders compared with other common methods under the same condition of software and hardware. Moreover, when average error is less than 10-3, the synchronization speed is 6500 times than common methods, the iteration needs only 4 times. The unknown parameters also were identified rapidly. The theoretical analysis and proof also were given.

In this paper, projective synchronization of different chaotic systems is studied, in the presence of uncertainties of system parameter variation, external noise disturbance and nonlinearity inputs. Using adaptive technique, sliding mode control method and pole assignment technique, an adaptive projective synchronization scheme is proposed to ensure the drive system and the response system with nonlinearity inputs can be rapidly synchronized up to the given scaling factor, without requiring the bounds of the system uncertainties and external noise disturbances be known in advance. The results of numerical simulation further verify the effectiveness and feasibility of the proposed scheme.