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Recently, many chaos-based image encryption algorithms have been proposed. Most of them adopt the traditional confusion-diffusion framework. Multiple encryption rounds or one round of complex encryption is typically executed in these schemes to realize high security. However, these operations will reduce the computational efficiency. To overcome these issues, we propose a novel key-substitution encryption architecture (KSA). Under the proposed KSA, we design a key scheming for updating the initial keys using the plain-image and develop a new substitution method for encrypting various types of images. The simulation results and security analysis demonstrate the superior security and high efficiency of the proposed image encryption algorithm using the KSA (KSA-IEA), which executes only one round of encryption.

Degree distribution lies at the heart of design an LT code. It affects the encoding and decoding complexity and error performance of LT code. In this paper, some metrics of welldesign LT code such as average degree, release probability, overhead factor is analyzed. It will compare the metrics among robust LT code, suboptimal LT code and SF-LT code. Moreover, it provides some mathematical guideline on how to design a well designed LT code.

This paper reports the characteristics and performance of a new type of Luby Transform codes, namely scale-free Luby Transform (SF-LT) codes. In the SF-LT codes, the degree of the encoded symbol follows a modified power-law distribution. Moreover, the complexity and decoding performance of SF-LT codes are compared with LT codes based on robust soliton degree distribution and LT codes based on suboptimal degree distribution. The results show that SF-LT codes outperform other LT codes in terms of the probability of successful decoding over an ideal channel and a binary erasure channel. Moreover, the encoding/decoding complexity for the SF-LT codes is superior.

To better control the scope of information propagation and understand its dynamic characteristics, we propose an information propagation model based on evolutionary game theory. The model can simulate an individual’s strategy selection in social networks when facing two pieces of competitive information, whereby “competitive information” is defined as two pieces of information which have the opposite meaning. First, a reasonable payoff function is designed for individuals based on pairwise interaction. Second, each individual selects a friend it trusts. Third, a probability value is used to indicate whether an individual imitates the strategy of the selected friend. In the model, we consider not only the heterogeneous influence of friends’ strategies on individual decision-making in the process of communication but also the attenuation of individuals’ attention to information when information about friends is received repeatedly. The simulation results show that our model can accurately simulate the propagation of two pieces of competitive information. Furthermore, we find that the basic payoff that accrues to individuals as a result of spreading their information and the network topology are two factors that significantly influence the propagation result. The results provide effective insights into how to better control and guide public opinion.

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We study herein the problem of the location of the information propagation source in social networks based on the network topology and a set of observations. We propose a concise and novel method to accurately locate the source of information using naming game theory. This study introduces the design of a dynamic deployment method that reduces considerably the number of observations and the time needed to locate the source. Moreover, it calculates the probability of each node that acts as a source based on the information provided by observations. This method can be potentially applied to various information propagation models. The simulation results reveal that the method is able to estimate the information source within a small number of hops from the true source.