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A novel bit-level image encryption algorithm based on 2D-LICM hyperchaotic map

A new hybrid digital chaotic system with applications in image encryption

Color image encryption based on hybrid hyper-chaotic system and cellular automata

A visually secure image encryption scheme based on compressive sensing

Image encryption based on three-dimensional bit matrix permutation

In this study, we describe a system-level multiple refactoring algorithm, which can identify the move method, move field, and extract class refactoring opportunities automatically according to the principle of “high cohesion and low coupling.” The algorithm works by merging and splitting related classes to obtain the optimal functionality distribution from the system-level. Furthermore, we present a weighted clustering algorithm for regrouping the entities in a system based on merged method-level networks. Using a series of preprocessing steps and preconditions, the “bad smells” introduced by cohesion and coupling problems can be removed from both the non-inheritance and inheritance hierarchies without changing the code behaviors. We rank the refactoring suggestions based on the anticipated benefits that they bring to the system. Based on comparisons with related research and assessing the refactoring results using quality metrics and empirical evaluation, we show that the proposed approach performs well in different systems and is beneficial from the perspective of the original developers. Finally, an open source tool is implemented to support the proposed approach.

Automatic Software Refactoring via Weighted Clustering in Method-Level Networks

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.

/pdf/evolutionary-game-dynamics-of-the-competitive-information-1n3axprbwt.pdf

Evolutionary Game Dynamics of the Competitive Information Propagation on Social Networks

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.

/pdf/efficient-and-secure-image-encryption-algorithm-using-a-22x2djo488.pdf

Efficient and Secure Image Encryption Algorithm Using a Novel Key-Substitution Architecture

Online fountain codes have been proven to require lower overhead and fewer feedbacks than growth codes for successful decoding. In an attempt to improve the intermediate symbol recovery rate, the authors propose sending a number of degree-1 input symbols prior to the build-up phase based on a simple application of probability theory. In addition, during the completion phase, received encoded symbols with three neighbouring white (un-decoded) symbols are retained for decoding and updating the decoding graph later. The performance and characteristics of the proposed improved online fountain codes are compared to those of the original online fountain codes over an erasure channel. Simulation results reveal that the improved online fountain codes outperform the original fountain codes in terms of intermediate symbol recovery rate, average encoded symbols required to be generated by the sender, average feedback transmissions, and encoding/decoding efficiency.

Yuli Zhao

Papers

Image encryption based on three-dimensional bit matrix permutation

Automatic Software Refactoring via Weighted Clustering in Method-Level Networks

Evolutionary Game Dynamics of the Competitive Information Propagation on Social Networks

Efficient and Secure Image Encryption Algorithm Using a Novel Key-Substitution Architecture

Improved online fountain codes