Abstract: The subject of the research is the problem of identifying and countering intrusions (attacks) in information security systems (ISS) based on the system-conceptual approach, developed within the framework of the RFBR funded project No. 19-01-00383. The object of the research is neural networks and information security systems (ISS) of automated data processing systems (ADPS). The authors proceed from the basic conceptual requirements for intrusion detection systems - adaptability, learnability and manageability. The developed intrusion detection procedure considers both internal and external threats. It consists of two subsystems: a subsystem for detecting possible intrusions, which includes subsystems for predicting, controlling and managing access, analyzing and detecting the recurrence of intrusions, as well as a subsystem for countering intrusions, which includes subsystems for blocking / destroying protected resources, assessing losses associated with intrusions, and eliminating the consequences of the invasion. Methodological studies on the development of intrusion detection procedures are carried out using artificial intelligence methods, system analysis, and the theory of neural systems in the field of information security. Research in this work is carried out on the basis of the achievements of the system-conceptual approach to information security in ADPS.The main result obtained in this work is a block diagram (algorithm) of an adaptive intrusion detection procedure, which contains protection means and mechanisms, built by analogy with neural systems used in security systems.The developed general structure of the intrusion detection and counteraction system allows systematically interconnecting the subsystems for detecting possible intrusions and counteracting intrusions at the conceptual level.

Keywords: automated data processing, information protection strategies, intrusion detection systems, information security support, information protection, intelligent systems, neural networks, adaptable systems, attack detection system, software information protection

Abstract: The subject of the research is lip seals with an elongated working part for sealing gaps with significant displacements of parts. There are many standard and catalog seals, but the increasing requirements for the maximum strokes of the mating parts require an expansion of the known series. This, in turn, requires more accurate calculations. The main reason for the failure of such seals is the loss of stability of their working part. The variant of action on external pressure seal is considered. This option is the most important, since the operating pressures are more than ten atmospheres, and the seal acts as an element of machine reliability. When pressure is applied from the inside of the seal, it acts as a boot or oil scraper, that is, it does not directly contribute to the reliability of the mechanism. The authors show the derivation of expressions for bending moments in the working part of the seal for the case taken. The scientific novelty lies in the fact that the problem of calculating elliptic integrals in the expression for the bending moment is solved geometrically by representing the working part of the seal in the form of an elliptical ring. The main conclusion is that the existing computational techniques, when supplemented with the found expressions, make it possible to construct a complete lip seal profile of the considered configuration. The practical significance lies in the fact that the construction of profiles according to the considered method can be easily automated using the parameterization tools built into popular CAD systems.

Keywords: elastomeric products, parameterization, mathematical modeling, mechanical engineering, lip seals, sealing technology, elliptical ring, computer-aided design, Castigliano's theorem, non-standard seals

Abstract: In this paper the design of a parametric tooth model is considered, with the help of which it is possible to study the development of dental pathology. This model allows you to create a tooth prosthesis, with minimal intervention of the dentist, by creating a three-dimensional image of the studied tooth, close in architecture to the real one. Particular attention is paid to the study of the geometry of the tooth - the second molar. Based on the analysis of the presented initial data, additional characteristics were introduced, due to which the geometry of the surface areas of the tooth model is calculated. The article discusses the advantages and disadvantages of visualization methods used in this area to solve problems associated with the analysis of complex and heterogeneous information, and also presents conclusions on practical and scientific results. A parametric model of a tooth was built, which describes its geometry in comparative detail. The main necessary parameters and their limitations are determined. The obtained calculations of the geometric shape of the tooth can be used to study and analyze the biomechanics of teeth, the principles of differential diagnosis of pain, planning future iatrogenic intervention, as well as algorithms for the treatment of prosthetic disorders, provides the doctor with all the necessary tools. The constructed crown part of the tooth in the AutoCAD system can be used for teaching dental students. This model can be used for scientific and practical activities of students on the modeling and restoration of dental crowns.

Keywords: elliptical surfaces, hyperboloid, ellipsoid, dental crown, molar, math modeling, prosthetics, parameterization, CAD, biomechanics of teeth

Abstract: The author considers a problem of automatic synthesis (induction) of the rules for transforming the natural language formulation of the problem into a semantic model of the problem. According to this model a program that solves this problem can be generated. The  problem is considered in relation to the system of generation, recognition and transformation of programs PGEN ++. Based on the analysis of literary sources, a combined approach was chosen to solve this problem, within which the rules for transforming the natural language formulation into a semantic model of the problem are generated automatically, and the specifications of the generating classes and the rules for generating a program from the model are written manually by a specialist in a specific subject area. Within the framework of object-event models, for the first time, a mechanism for the automatic generation of recognizing scripts and related entities (CSV tables, XPath functions) was proposed. Generation is based on the analysis of the training sample, which includes sentences describing objects in the subject area, in combination with instances of such objects. The analysis is performed by searching for unique keywords and characteristic grammatical relationships, followed by the application of simple eliminative-inducing schemes. A mechanism for the automatic generation of rules for replenishing / completing the primary recognized models to full meaning ones is also proposed. Such generation is performed by analyzing the relations between the objects of the training sample, taking into account information from the specifications of the classes of the subject area. The proposed schemes have been tested on the subject area "Simple vector data processing", the successful transformation of natural language statements (both included in the training set and modified) into semantic models with the subsequent generation of programs solving the assigned tasks is shown.

Keywords: XPath-functions, domain-specific language, grammar parsing, training sample, eliminative induction, rules induction, code synthesis, program generation, natural-language processing, regular expressions

Abstract: The subject of the research is the process of collecting and preliminary preparation of data from heterogeneous sources. Economic information is heterogeneous and semi-structured or unstructured in nature. Due to the heterogeneity of the primary documents, as well as the human factor, the initial statistical data may contain a large amount of noise, as well as records, the automatic processing of which may be very difficult. This makes preprocessing dynamic input data an important precondition for discovering meaningful patterns and domain knowledge, and making the research topic relevant.Data preprocessing is a series of unique tasks that have led to the emergence of various algorithms and heuristic methods for solving preprocessing tasks such as merge and cleanup, identification of variablesIn this work, a preprocessing algorithm is formulated that allows you to bring together into a single database and structure information on time series from different sources. The key modification of the preprocessing method proposed by the authors is the technology of automated data integration.The technology proposed by the authors involves the combined use of methods for constructing a fuzzy time series and machine lexical comparison on the thesaurus network, as well as the use of a universal database built using the MIVAR concept.The preprocessing algorithm forms a single data model with the ability to transform the periodicity and semantics of the data set and integrate data that can come from various sources into a single information bank.

Keywords: time series, MIVAR, fuzzy time series, forecasting, clearing data, data unification, preprocessing, machine learning, data mining, knowledge base