Biblio
This paper considers the complex of models for the description, analysis, and modeling of group behavior by user actions in complex social systems. In particular, electoral processes can be considered in which preferences are selected from several possible ones. For example, for two candidates, the choice is made from three states: for the candidate A, for candidate B and undecided (candidate C). Thus, any of the voters can be in one of the three states, and the interaction between them leads to the transition between the states with some delay time intervals, which are one of the parameters of the proposed models. The dynamics of changes in the preferences of voters can be described graphically on diagram of possible transitions between states, on the basis of which is possible to write a system of differential kinetic equations that describes the process. The analysis of the obtained solutions shows the possibility of existence within the model, different modes of changing the preferences of voters. In the developed model of stochastic cellular automata with variable memory at each step of the interaction process between its cells, a new network of random links is established, the minimum and the maximum number of which is selected from a given range. At the initial time, a cell of each type is assigned a numeric parameter that specifies the number of steps during which will retain its type (cell memory). The transition of cells between states is determined by the total number of cells of different types with which there was interaction at the given number of memory steps. After the number of steps equal to the depth of memory, transition to the type that had the maximum value of its sum occurs. The effect of external factors (such as media) on changes in node types can set for each step using a transition probability matrix. Processing of the electoral campaign's sociological data of 2015-2016 at the choice of the President of the United States using the method of almost-periodic functions allowed to estimate the parameters of a set of models and use them to describe, analyze and model the group behavior of voters. The studies show a good correspondence between the data observed in sociology and calculations using a set of developed models. Under some sets of values of the coefficients in the differential equations and models of cellular automata are observed the oscillating and almost-periodic character of changes in the preferences of the electorate, which largely coincides with the real observations.
The aim of this paper is to find cellular automata (CA) rules that are used to describe S-boxes with good cryptographic properties and low implementation cost. Up to now, CA rules have been used in several ciphers to define an S-box, but in all those ciphers, the same CA rule is used. This CA rule is best known as the one defining the Keccak $\chi$ transformation. Since there exists no straightforward method for constructing CA rules that define S-boxes with good cryptographic/implementation properties, we use a special kind of heuristics for that – Genetic Programming (GP). Although it is not possible to theoretically prove the efficiency of such a method, our experimental results show that GP is able to find a large number of CA rules that define good S-boxes in a relatively easy way. We focus on the 4 x 4 and 5 x 5 sizes and we implement the S-boxes in hardware to examine implementation properties like latency, area, and power. Particularly interesting is the internal encoding of the solutions in the considered heuristics using combinatorial circuits; this makes it easy to approximate S-box implementation properties like latency and area a priori.
Cellular Automata based computing paradigm is an efficient platform for modeling complicated computational problems. This can be used for various applications in the field of Cryptography. In this paper, it is used for generating a DNA cryptography based encryption algorithm. The encoded message in binary format is encrypted to cipher colors with the help of a simple algorithm based on the principles of DNA cryptography and cellular automata. The message will be in compressed form using XOR operator. Since cellular automata and DNA cryptographic principles are exploited, high level of parallelism, reversibility, uniformity etc. can be achieved.
In this paper we investigate the proposals made by various industries for the Cellular Internet of Things (C-IoT). We start by introducing the context of C-IoT and demonstrate how this technology is closely linked to the Low Power-Wide Area (LPWA) technologies and networks. An in-depth look and system level evaluation is given for each clean slate technology and a comparison is made based on its specifications.
In this paper we investigate the proposals made by various industries for the Cellular Internet of Things (C-IoT). We start by introducing the context of C-IoT and demonstrate how this technology is closely linked to the Low Power-Wide Area (LPWA) technologies and networks. An in-depth look and system level evaluation is given for each clean slate technology and a comparison is made based on its specifications.