A general model of the origin and evolution of chaotic wave processes in electrochemically active neuronal media based on the proposed method of matrix decomposition of operators of nonlinear systems has been developed. The mathematical models of Hodgkin – Huxley and FitzHugh – Nagumo of an electrochemically active neuronal media are considered. The necessary conditions for self-organization of chaotic self-oscillations in the FitzHugh – Nagumo model are determined. Computer modeling based on the matrix decomposition of chaotic wave processes in electrochemically active neuronal media has shown the interaction of higher-order nonlinear processes leading to stabilization (to a finite value) of the amplitude of the chaotic wave process. Mathematically, this is expressed in the synchronous “counteraction” of nonlinear processes of even and odd orders in the general vector-matrix model of an electrochemically active neuronal media being in a chaotic mode. It is noted that the state of hard self-excitation of nonlinear oscillations in an electrochemically active neuronal media leads to the appearance of a chaotic attractor in the state space. At the same time, the  proposed vector-matrix model made it possible to find more general conditions for the appearance and evolution of chaotic wave  processes in  comparison with  the  initial  Landau  turbulence model  and,  as  a  result,  to  explain  the occurrence of consistent nonlinear phenomena in an electrochemically active neuronal media.

One of the key problems in developing and integrating expert systems for medical research is the problem of data aggregation. Most of the times, general information about the patient and data about undergone research procedures exist as part of several disconnected information systems, each using its own schema for presenting and storing information. The paper proposes a solution to aggregate research and patient data in medical establishments using formal projections mechanism, which allows to unify data extraction from separate data sources. Graph-based patient and research record representation is introduced, which allows to support and optimize complex queries for single patient and for a set of historical data from single research. Proposed representation mechanism is also shown to be effective for centralized processing using various data mining and intelligent analysis techniques.

The problem of decomposition of a Boolean function is to represent a given Boolean function in the form of a superposition of some Boolean functions whose number of arguments are less than the number of given function. The bi-decomposition represents a given function as a logic algebra operation, which is also given, over two Boolean functions. The task is reduced to specification of those two functions. A method for bi-decomposition of incompletely specified (partial) Boolean function is suggested. The given Boolean function is specified by two sets, one of which is the part of the Boolean space of the arguments of the function where its value is 1, and the other set is the part of the space where the function has the value 0. The complete graph of orthogonality of Boolean vectors that constitute the definitional domain of the given function is considered. In the graph, the edges are picked out, any of which has its ends corresponding the elements of Boolean space where the given function has different values. The problem of bi-decomposition is reduced to the problem of a weighted two-block covering the set of picked out edges of considered graph by its complete bipartite subgraphs (bicliques). Every biclique is assigned with a disjunctive normal form (DNF) in definite way. The weight of a biclique is a pair of certain parameters of   assigned DNF. According to each biclique of obtained cover, a Boolean function is constructed whose arguments are the variables from the term of minimal rank on the DNF. A technique for constructing the mentioned cover for two kinds of output function is described.

The problem of partitioning a logical circuit into subcircuits is considered. It is of great importance when performing optimization transformations in the process of circuit synthesis. The brief review of partitioning methods and algorithms is given, and two groups of algorithms are identified: constructive and iterative one. The interpretation of a logical circuit in the form of a graph is presented. The problem of partitioning in terms of a graph-theoretic model is defined and some algorithms for solving the partitioning problem are proposed. Logic circuit functions are defined by a system of logical equations. Algorithms perform the partitioning the system of logical equations into subsystems with the restrictions of the number of input and output variables. The data structures to execute the algorithms are defined. Various types of equations connections, obtaining better solutions for partitioning are described. The problems of the use of partitioning algorithms to improve the quality of the circuit at the stage of technology-independent optimization are investigated. The results of an experimental study carried out by the BDD optimization procedure for the functional description of the circuit and LeonardoSpectrum synthesis confirm the effectiveness of the developed algorithms. The algorithms are implemented as partitioning circuit procedures in the experimental FLC system for logical design.

The article discusses distributed infocommunication networks, in which the interaction of users, application servers and databases is carried out. When accessing an infocommunication network, the first procedure is to authenticate the agents through their authentication by password mechanism. It is shown that for social networks with a large number of users, widely used assessment of the security of password systems based on the calculation of the determination probability is not sufficient. The probability of the same passwords for two users with a password length of 6, 7 and 8 characters with alphabet size of 36, 42 and 57 characters and the number of users no more than 10 million is shown. An assessment of the strength of password authentication systems for info-communication networks based on the "birthday paradox" criterion is given. It has been determined that well-known social networks with a number of users comparable to the number of passwords used are not resistant to "birthday attacks". It is shown that for such systems the resistance of the password system to cracking should be assessed by  m=A^n/2      criterion.

Based on the analysis of vulnerability data for web resources and the CVSS metric, the distribution of the average CVSS (Common Vulnerability Scoring System standard for calculating a numerical vulnerability score on a ten-point scale) score for the websites of theRepublicofBelaruswas studied. The hypothesis on the distribution of the CVSS vulnerability assessment according to Poisson's law was tested by chi-square criteria. It was found that about 10% of web resources from the original general of samples of 19000 size have a critical averaged assessment level of vulnerability. As part of this work an universal system for collecting technical information about active web resources on the Internet from public directories and registries has been developed. Specific search templates have been developed using RegExp JavaScript expressions to detect the versions of technologies that were used to create websites. Based on this data the percentage distribution of used technologies, top-level domains and the geographical location of the servers were calculated. Proposed system can be adapted to any unique conditions required by information security specialists to conduct a security audit of web resources.

The paper proposes effective method of computer network protection from data exfiltration by the system of domain names. Data exfiltration by Domain Name System (DNS) is an approach to conceal the transfer of confidential data to remote adversary using data encapsulation into the requesting domain name. The DNS requests that transfer stolen information from a host infected by malicious software to an external host controlled by a malefactor are considered. The paper proposes a method of detecting such DNS requests based on text classification of domain names by convolutional neural network. The efficiency of the method is based on assumption that domain names exploited for data exfiltration differ from domain names formed from words of natural language. To classify the requests in convolutional neural network the use of character embedding for representing the string of a domain name is proposed. Quality evaluation of the trained neural network used for recognition of data exfiltration through domain name system using ROC-analysis is performed.

The paper presents the software architecture used for deployment of trained neural network into existing infrastructure of the domain name system targeting practical computer networks protection from data exfiltration. The architecture implies creation of response policy zones for blocking of individual requests, classified as malicious.

The quantitative characteristics of information resources for automated information systems (AIS) are proposed in the paper. The entities represented in the AIS by the information object mappings and their components (information unit and information element) are considered. The composition of the system information space is substantiated, which represents the whole amount of information being processed in the system, auxiliary information resources and all data of the system and its users. Application of the quantitative values to AIS information resources characteristics, taking into account the sense properties of information objects being mapped in AIS, will make it possible to raise the design decision making quality of AIS and its performance within the lifecycle.

The Internet continues to grow at a fast pace with over 1.5 billion websites in 2019 as compared with only one in 1991. The emergence of enormous websites of various complexities and types makes assessing the quality of these sites a vastly important, difficult and complicated task. With this concern, the current paper proposes a novel approach for website assessment by developing a new Website Quality Evaluation Methodology Universal Star (WQEMUS) with a theoretical and empirical basis. It became possible through the employment of the  grounded  theory  methodology  that  enables  relevant  concepts  to  emerge  from  data. To improve the reliability and validity of the findings, an extensive literature review, in-depth and qualitative interviews, and a user evaluation survey were conducted and associated together. In this way, the study presents the results of the selection and categorization of generic quality attributes for WQEMUS with a three-tier structure, consisting of top-level quality criteria, sub-criteria and indicators. These quality dimensions are grounded on a combination of subjective and objective indicators. Consequently, WQEMUS becomes capable of estimating a wide range of different websites irrespective of domain affiliation and services they provide, including Web 3.0 sites.

The results of the development of hardware and software system (micromodule), which detects and classifies underlying surface images of the Earth are presented. The micromodule can be installed on board of a light unmanned aerial vehicle (drone). The device has the size 5.2×7.4×3.1 cm, the weight52 g, runs on a Raspberry Pi Zero Wireless single-board microcomputer and uses a convolutional neural network based on MobileNetV2 architecture for real-time image classification. When developing the micromodule, the authors aimed to achieve a real-time image classification on inexpensive mobile equipment with low computing power so that the classification quality is  comparable  to  popular  deep  convolutional  network  architectures. The provided information could be useful for engineers and researchers who are developing compact budget mobile systems for processing, analyzing and recognition of images.