Applying causality principles to the axiomatization of probabilistic cellular automata

Cellular automata (CA) consist of an array of identical cells, each of which may take one of a finite number of possible states. The entire array evolves in discrete time steps by iterating a global evolution G. Further, this global evolution G is required to be shift-invariant (it acts the same everywhere) and causal (information cannot be transmitted faster than some fixed number of cells per time step). At least in the classical, reversible and quantum cases, these two top-down axiomatic conditions are sufficient to entail more bottom-up, operational descriptions of G. We investigate whether the same is true in the probabilistic case. Keywords: Characterization, noise, Markov process, stochastic Einstein locality, screening-off, common cause principle, non-signalling, Multi-party non-local box.Comment: 13 pages, 6 figures, LaTeX, v2: refs adde

CAST – City analysis simulation tool: an integrated model of land use, population, transport and economics

The paper reports on research into city modelling based on principles of Science of Complexity. It focuses on integration of major processes in cities, such as economics, land use, transport and population movement. This is achieved using an extended Cellular Automata model, which allows cells to form networks, and operate on individual financial budgets. There are 22 cell types with individual processes in them. The formation of networks is based on supply and demand mechanisms for products, skills, accommodation, and services. Demand for transport is obtained as an emergent property of the system resulting from the network connectivity and relevant economic mechanisms. Population movement is a consequence of mechanisms in the housing and skill markets. Income and expenditure of cells are self-regulated through market mechanisms and changing patterns of land use are a consequence of collective interaction of all mechanisms in the model, which are integrated through emergence

Key dependent dynamic S-Boxes on 3D cellular automata for block cipher

Substitution boxes (S-Boxes) are critical components of numerous block ciphers deployed for nonlinear transformation in the cipher process where the nonlinearity provides important protection against linear and differential cryptanalysis. Classical S-Boxes are represented by predefine fixed table structures which are either use for Data Encryption Standard (DES) or Advanced Encryption Standard (AES). Based on cryptanalysis, it does not offer sufficient cipher protections. The S-boxes used in encryption process could be chosen to be key-dependent. For secure communication, we need a better design of S-boxes to be used for encryption and decryption. In this paper we proposed key dependent dynamic 3D cellular automata (CA) S-Boxes for block ciphers. Our work is based on the design of AES S-Boxes which are originally in 2D presentation. The conceptual framework of the 3D CA S-Boxes is to convert and apply the 3D CA rule to static AES S-Boxes. The methodology is to do conversion from the AES S-Boxes into 3D array of (8x8x4) S-boxes, and then applies the 3D CA Von Neumann rules to them. After a 3D array is obtained from the AES S-Box, the 3D CA is applied based on the round key. The 3D array S-Box are then converted back to the 2D array S-Box and finally it is improved to meet the requirements of good S-Boxes. The obtained S-Boxes is called key dependent dynamic 3D CA S-Boxes having interesting features with dynamic stretchy arrangement, which is functionally understood by CA. Our proposed 3D CA S-boxes are better in comparison with the AES S-Boxes with predefined fixed table structures. Experimental results shown that the proposed 3D CA S-Boxes have secure characteristics like nonlinearity, SAC, BIC and algebraic degree. The proposed S-Boxes can be implemented in any block cipher for secure communication