Secure steganographic communication algorithm based on self-organizing patterns

Information Hiding Based on Statistical Features of Self-Organizing Patterns

A computational technique for the determination of optimal hiding conditions of a digital image in a self-organizing pattern is presented in this paper. Three statistical features of the developing pattern (the Wada index based on the weighted and truncated Shannon entropy, the mean of the brightness of the pattern, and the p-value of the Kolmogorov-Smirnov criterion for the normality testing of the distribution function) are used for that purpose. The transition from the small-scale chaos of the initial conditions to the large-scale chaos of the developed pattern is observed during the evolution of the self-organizing system. Computational experiments are performed with the stripe-type patterns, spot-type patterns, and unstable patterns. It appears that optimal image hiding conditions are secured when the Wada index stabilizes after the initial decline, the mean of the brightness of the pattern remains stable before dropping down significantly below the average, and the p-value indicates that the distribution becomes Gaussian.

Spatial dynamics in a predator-prey model with herd behavior

In this paper, a spatial predator-prey model with herd behavior in prey population and quadratic mortality in predator population is investigated. By the linear stability analysis, we obtain the condition for stationary pattern. Moreover, using standard multiple-scale analysis, we establish the amplitude equations for the excited modes, which determine the stability of amplitudes towards uniform and inhomogeneous perturbations. By numerical simulations, we find that the model exhibits complex pattern replication: spotted pattern, stripe pattern, and coexistence of the two. The results may enrich the pattern dynamics in predator-prey models and help us to better understand the dynamics of predator-prey interactions in a real environment.

Spatial dynamics in a predator-prey model with Beddington-DeAngelis functional response

In this paper spatial dynamics of the Beddington-DeAngelis predator-prey model is investigated. We analyze the linear stability and obtain the condition of Turing instability of this model. Moreover, we deduce the amplitude equations and determine the stability of different patterns. In Turing space, we found that this model has coexistence of H(0) hexagon patterns and stripe patterns, H(π) hexagon patterns, and H(0) hexagon patterns. To better describe the real ecosystem, we consider the ecosystem as an open system and take the environmental noise into account. It is found that noise can decrease the number of the patterns and make the patterns more regular. What is more, noise can induce two kinds of typical pattern transitions. One is from the H(π) hexagon patterns to the regular stripe patterns, and the other is from the coexistence of H(0) hexagon patterns and stripe patterns to the regular stripe patterns. The obtained results enrich the finding in the Beddington-DeAngelis predator-prey model well.