A Comparative Study between the Dynamic Behaviours of Standard Cellular Automata and Network Cellular Automata Applied to Cryptography

Abstract

The dynamical behavior of cellular automata (CA) transition rules are objects of study for different knowledge fields. This paper is about the development of cryptographic methods using CA-like transition rules. We investigate the dynamic behavior of rules that are not able to propagate a perturbation inserted in the initial lattice considering variations of the regular connection structure of CAs that are akin to the small-word network construction process. Extensive experimental results indicate that such modifications in the CA connection structure will produce large changes in the dynamic behavior of the evaluated rules, suggesting that it is possible to increase considerably the space of possible cryptographic keys to methods based on CA rules, provided a different topological construct for the CA lattice is considered. C 2015 Wiley Periodicals, Inc.

Autômatos celulares unidimensionais caóticos com borda fixa aplicados à modelagem de um sistema criptográfico para imagens digitais

“…No entanto, esse modelo apresenta a desvantagem do paralelismo ser quebrado devido à utilização de pilhas de armazenamento global e local que guarda as possíveis pré-imagens. Outros modelos foram posteriormente estudados nessa temática Macedo [13], Barros [2], no entanto, não são estratégias puramente baseadas no cálculo de pré-imagens altamente paralelizáveis de ACs.…”

Tracing the spatial‐temporal evolution dynamics of air traffic systems using graph theories

“…By modeling a complex system as a network is every straightforward as the nodes and edges of the network can depict the structural properties of the studied system. 10,11 The most important thing is that modeling a complex system as a network can provide a systemic view toward the understanding of the focal complex system. [12][13][14] To trace the spatial-temporal evolution dynamics of air traffic systems, scientists normally model the air traffic systems as spatial-temporal networks and then apply network theories to probe the evolution dynamics of the modeled air traffic systems.…”

“…A graph, also known as a network, is composed of a set of nodes and edges. By modeling a complex system as a network is every straightforward as the nodes and edges of the network can depict the structural properties of the studied system 10,11 . The most important thing is that modeling a complex system as a network can provide a systemic view toward the understanding of the focal complex system 12–14 …”

Butterfly Effect in Chaotic Image Segmentation

“…Different neighbourhood topologies (lattice, network, small-worlds) have been investigated in order to study their influence on the rule performance. In [8][9][10][11][12][13], the neighbourhood topologies are evolved for cellular automata. In these studies a better performance of evolved topologies over the regular lattices in CA majority and synchronization tasks was shown.…”