№ 4 (56)

The purpose of the work: to develop a methodology for controlling the circulation of digital financial assets, other digital rights and digital currency to combat corruption based on the analysis of cryptocurrency transactions. Research methods: methods of analysis, comparison, generalization, structural decomposition from the theory of system analysis, machine learning methods. Result obtained: an analysis of the technological possibilities of controlling the circulation of digital financial assets, other digital rights, digital currency was carried out. A new method for controlling the circulation of digital financial assets, other digital rights and digital currency to combat corruption is proposed based on the analysis of cryptocurrency transactions using machine learning methods. A comparison and evaluation of the accuracy of various machine learning methods was carried out: logistic regression, random forest, ensemble methods. A software prototype has been developed that allows for intellectual analysis and control of cryptocurrency transactions. Scientific novelty: a new method for analysing control over the circulation of digital financial assets, other digital rights and digital currency to combat corruption based on the analysis of cryptocurrency transactions, based on big data processing technologies and machine learning methods, is proposed. Contribution of co-authors: Feklin V.G. - analysis of technological capabilities to control the circulation of digital financial assets, other digital rights, digital currency, development of algorithms; Solovyov V.G. - development of a method for controlling the circulation of digital financial assets, general project management; Korchagin S.A. - preparation and analysis of data, software implementation of methods for intellectual analysis and control of cryptocurrency transactions; Tsaregorodtsev A.V. - development of a methodology for analysis of cryptocurrency transactions.
Keywords: digital assets, cryptocurrency transactions, intelligent system, machine learning methods.

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Purpose of the article: The paper examines the application of topological data analysis to identify and classify patterns of user behavior of corporate information resources in cybersecurity tasks.
Method: the study is based on mathematical concepts of the theory of persistence homologies (simplex complexes, persistence diagrams, filtering functions, topological descriptors), theoretical models of metric spaces.
Result: A formalized definition of topological features is given, properties and relation of Betti curves with persistence diagrams and other known topological descriptors used in topological data analysis are disclosed. The results of practical testing on the time-series data presented in the monitoring system of corporate network users’ work with corporate information resources, confirm that the use of positively defined step functions to construct Betti curves provides an acceptable computational complexity of the procedures required to identify and classify user behavioral patterns. The approach proposed based on topological descriptors and modified desirability functions Harrington functions allows to reliably capture user activity deviation from a typical behavioral pattern, potentially constituting a security incident. Scientific novelty: is the application of topological data analysis using Betti curves to identify and classify user behavior patterns of corporate information resources.
Keywords:  cybersecurity, UEBA, topological data analysis, Betti curves, time series.

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The purpose of the article: adaptation of the logical-probabilistic method of evaluating complex systems to the tasks of building information security systems in a multi-agent system. Research method: during the research, the main provisions of the methodology of structural analysis, system analysis, decision theory, methods of evaluating events under the condition of incomplete information were used. The result: in this article, it is proposed to consider the issues of information security based on the analysis of the relationship between the subjects and the object of protection. The types of relations “subject-subject”, “subject-object” are defined and the basic axiomatics of relations is given, taking into account the requirements for information protection. Based on axiomatics, formal logical definitions of the main elements of information security are given: violator, defender, user, internal violator, attack, defense, confrontation. According to the results of the analysis of relations, it is shown that the violator and the defender use a single source of information for decision-making, but at the same time their activities in assessing the situation and choosing actions are asymmetric. The analysis of the relations made it possible to give a formal logical description of the processes of interaction of subjects with each other and with the object of protection. What is the basis for the allocation of fractal structures in the information system. Scientific novelty: consideration of information security issues using the apparatus of mathematical and logical relations. Development of formal logical expressions describing the interaction of the violator and the defender with each other, as well as with the object of protection.
Keywords:  information security model, assessment of complex systems, logical-probabilistic method, theory of
relations, system analysis.

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Purpose of the work: improving the security of data processing in cloud services through the development and application of methods and algorithms for homomorphic encryption. Research methods: analysis of a possible implementation of the Gaussian elimination method using homomorphic encryption, analysis of existing problems in implementing a homomorphic implementation for the Gaussian elimination method. Research results: analysis of the possibility of performing a homomorphic implementation of the solution of a system of linear algebraic equations (SLAE) by the Gaussian elimination method was performed; problems that arise due to the specifics of the task are noted - the processed data is encrypted and the control algorithm does not have access to it; the solution of the noted problems is proposed; an algorithm for the homomorphic implementation of the Gaussian elimination method is proposed, which allows solving the SLAE over homomorphically encrypted data and obtaining a homomorphically encrypted result containing the numerical solution of the SLAE, as well as an error bit indicating the incompatibility of the system or an infinite number of solutions; the analysis is carried out and the best variant of the ciphertext representation is proposed, which allows avoiding the growth of the ciphertext when solving SLAE containing a large number of variables; the analysis of the proposed implementation is carried out and possible improvements that increase the speed of data processing are considered. Scientific novelty: an algorithm for the homomorphic implementation of the Gaussian elimination method for solving SLAE is proposed, which can be used in cloud services for secure data processing. The algorithm can be used to solve SLAE in its pure form, or as a step of another algorithm.
Keywords:  information security, cryptographic protection, homomorphic cryptography, secure computing, cloud
computing, methods and algorithms.

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Purpose: The aim of the work is to develop a mutual authentication protocol for a group of objects with a dynamic topology (for example, for a swarm of unmanned aerial vehicles (UAVs)), which jointly perform a common task. It is important to take into account that each individual object of the group has a limited energy reserve. It is necessary to take into account the fact that an object can be disconnected from the network and then reconnected to it, so the protocol must provide a way to re-authenticate the objects of the group mutually. Also, objects must be able to transmit data to the control node, which is called the base station (BS). When designing a protocol, it is important to take into account that the risks of opening the transmitted information should be minimized if an attacker gains physical access to the group object's memory.
Method: The method is based on the use of the mathematical apparatus of probability theory, mathematical statistics, information theory, cryptography. As cryptographic primitives, a pseudo-random sequence generator, hash functions, symmetric encryption, and a physically non-cloneable function are used.
Results: The analysis of existing approaches to mutual authentication and data transfer in a group of objects with dynamic topology is carried out. A UAV mutual authentication protocol is proposed, which solves a number of important tasks, such as: dynamic change of the encryption key, absence of highly loaded calculations for dynamic network elements, scalability, and the possibility of data exchange between network participants. The developed protocol is based on the use of several basic algorithms: an algorithm for constructing a spanning tree, an algorithm for performing UAV mutual authentication and organizing data transfer, and an algorithm for performing UAV authentication in front of the BS. A simulation example is provided to illustrate the developed solution with dedicated phases and analyze the transmission of messages in it within two UAVs. The scientific novelty primarily lies in the fact that in the developed authentication protocol, special attention is paid to the problem of stability of the authentication scheme and reconfiguration of the UAV network, and also takes into account the problem of low computing power, most of the highly loaded calculations that occupy the processor are transferred to the BS - the most powerful computing element of the network . The above solution ensures the change of the session key with the presence of a minimum of pre-established information and the constant updating of the key between network elements.
Keywords: unmanned aerial vehicle, base station, authentication, cryptography, encryption, pseudo-random
number, spanning tree, network, hash function, timestamp, request, response, scalability, fault tolerance.

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19. Borisov K.V., Ljubushkina I.E., Panasenko S.P. i dr. Sposob, sistema i ustrojstvo kriptograficheskoj zashhity kanalov svjazi bespilotnyh aviacionnyh kompleksov // Patent №2704268, opublikovan 25.10.2019 — https://i.moscow/patents/ru2704268c1_20191025

The task of ensuring secure storage and data transmission in information systems is becoming more relevant nowadays due to digitalization processes that are actively integrating into all areas of people activity. The medical industry requires special attention, especially, the task of ensuring the security of patient data, who are users of medical information systems (MIS). Purpose of the work: development of a method for ensuring data security in terms of transferring and storage of personal patients' data who use the MIS which have built based on distributed cloud architecture. Research method: the analysis of possible ways to ensure personal data security in distributed information systems based on a secret sharing protocol. The analysis of existing problems in terms of protection methods implementation in cloud-based systems. Analysis of violator model and attack methods.
Results: in terms of this paper, the use of a secret sharing protocol was justified as the basis for a method of ensuring the protection of patients' personal data in a cloud-based medical information system. Among several candidates with a similar functionality, the optimal secret sharing scheme was determined, taking into account the specifics of the task. The choice of the scheme has justified by the presence of such advantages as the properties of perfection, ideality, as well as the speed of execution the basic operations over other candidates. The experiments have been performed and the results have been obtained that have confirmed the correct choice of the secret sharing scheme (Shamir). Based on the chosen scheme, an implementation of the method for ensuring the security of patients' personal data in cloud medical information system has proposed. The authors proposed a cloud medical system architecture that allows to integrate a protection mechanism to be able to test how the proposed method works.
Keywords: encryption, cryptography, cloud computing security, personal data protection, secret sharing scheme,
information systems.

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The purpose of the article: analysis of sensitivity of structural and parametric metrics of networks with adaptive topology to computer attacks of different types. Main research methods: system analysis of existing structural metrics to assess the state of computer networks, theoretical formalization, conducting an experiment.
Result: the proposed approach allowed us to estimate in practice the impact of various types of computer attacks, specific to networks with adaptive topology, in particular, insomnia type attacks, sinkhole and Sybil attacks. Practical modeling of adaptive network infrastructure using graph theory has yielded a unique dataset that allows us to compute both structural and parametric methods for assessing network state. Also, the proposed approach, which combines the simultaneous estimation of structural and parametric metrics for network nodes, demonstrated flexibility in terms of recognizing various network attacks, some of which are more clearly manifested in network traffic, and another part in changes in the network topology. Extension of the proposed approach in terms of used metrics will allow to evaluate the security of the current state of the network at three levels: at the level of the entire network or its individual segments (structural metrics), at the level of critical nodes (structural and parametric metrics) and at the level of devices (parametric metrics). Scientific novelty: by means of simulation using graph theory a new data set has been created, which contains the characteristics of networks with adaptive network topology functioning in normal conditions and under the influence of specific computer attacks. The key difference from the known simulation models of dynamic networks and the data sets formed on their basis is the ability to simultaneously analyze the network data exchanged by nodes, the physical performance of the nodes and the structure of the network.
Keywords: Computer attacks, networks with adaptive topology, centrality metrics, signal level, Smart Grid networks, sinkhole attack, Sybil attack.

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Aim: development of a mathematical model of the vector of a DDoS attack on the network infrastructure of an Industrial Control System to estimate the average time of its successful implementation. Research method: a mathematical model of the DDoS attack vector was built using the method of topological transformation of stochastic networks. The verification of the obtained calculated data was carried out using an experimental stand that simulates the operation of a network of an Industrial Control System and is under the influence of a DDoS attack.
Result: a model of an intruder that organizes a DDoS attack on the network of an Industrial Control System has been developed, which is a sequence of actions of the intruder and the processes he creates. The dependencies of the processes created by the intruder and the probabilistic transitions between them are described. The input parameters of the mathematical model are defined as the average duration of each of the processes. Based on the processes described in the intruder’s model, a stochastic network was compiled, and a characteristic equation was constructed that allows obtaining an approximate function of the DDoS attack vector. The output data is obtained in the form of the average time of a successful DDoS attack, as well as the dependence of the probability of a successful DDoS attack on its duration in time. At the stand “Information security in industrial systems” several experiments were carried out that implement a DDoS attack and allow us to conclude that the real time of a successful DDoS attack is consistent with the one calculated using the constructed mathematical model. Scientific novelty of the research: a mathematical model of the vector of a DDoS attack on the network infrastructure of an Industrial Control System has been developed, which is distinguished using the method of topological transformation of a stochastic network to build an intruder model and estimate the average time of a successful DDoS attack, regardless of its type and intensity. The developed model differs from the existing ones by the absence of the need to consider a certain type of DDoS attack and its intensity, as well as by the presence of an estimate of the duration of the intruder’s preliminary actions.
Keywords: Industrial Control System (ICS), information protection, cyberattack, mathematical model, intruder model, topological transformation of a stochastic network.

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The goal of the study is to create a method of detecting attacks on complex objects and processes by evaluating and predicting their state; the method is based on 7 principles proposed by the authors earlier; a feature of method is its invariance with respect to the genesis of attacks. Research methods: system analysis, analytical modeling methods, statistical methods and machine learning, software code development for the implementation of estimation and prediction algorithms.
Result: proposed method of attack detection on a complex object that uses assessment of current and future prediction states; the description of method is given in schematic and analytical form using a cross-cutting example from information security field; theoretical significance lies in the scientific and methodological apparatus of assessment and prediction development of states different structure objects; the practical significance lies in the possibility of direct implementation of software prototype with potentially high efficiency. In the second part of the paper all stages of the method are algorithmized, which allows us to obtain an analytical model of attack detection. A methodology for managing the detection process, developed in the interests of practical application of the proposed scientific and methodological apparatus, is presented. The course of the experiment on the application of the method for a hypothetical example of attacks on a network node is described. The degree of utilization of the 7 principles developed by the authors in previous studies, which form the basis of the methods of estimating and predicting the state of complex objects, is shown. The scientific novelty is to create a method of detecting attacks on a complex object (or process), which is based on a fundamentally new approach to the evaluation and prediction of its state, obtained by the authors in previous studies. As a result, this method is applicable to subject area without taking into account its specificity, which in particular is achieved through the use of author’s original intellectual fuzzy graph-oriented model. In contrast to the large number of information systems attacks detection methods, this method is described not only in terms of graphical scheme and steps sequence, but also using analytical record of algorithms that allows to apply to it certain mathematical apparatuses (for example, to justify the performance or optimization of individual steps).
Keywords: information technology, information security, complex object, complex process, attack detection method, analytical algorithm, experiment.

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The research aims to develop approach to ensure the cybersecurity of the information and communication infrastructure of the energy community. The research relies on the multi-agent reinforcement learning, Markov processes, probabilistic methods. Research result: Potential threats and vulnerabilities of the information and communication infrastructure of the microgrid community are analyzed. A proposed model of microgrid coalitions take into account such factors as cybersecurity risks, the mutual influence of available microgrid resources to protect against cyber-attacks, and the mutual influence of the consequences of cyber threats. The developed method determines the effectiveness of protection against cyber threats with and without coalitions for the microgrid community. Research result: ways of forming energy communities are considered, various structures for managing such communities are analyzed, threats and vulnerabilities of information systems, possible failures and faults during cyber-attacks that can lead to errors in the formation of control actions are identified. An approach has been developed to ensure the cybersecurity of interconnected information systems of the microgrid community. The scientific novelty lies in the fact that in order to ensure the cybersecurity of information and communication infrastructure with multi-agent management of the energy community of microgrids, an approach is proposed, the methodology of which is to model the energy community, simulate cyber-attacks, assess the consequences of cyber-attacks and develop methods and means of protecting interdependent information systems from cyber-attacks.
Keywords:  distributed energy, energy community, microgrid, multi-agent management, cybersecurity risks, cyber-attack models.

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Purpose of work: research of methods for detecting internal threats to information security and improving their effectiveness through the modernization of the approach to building an internal threat detection system. Research method: system analysis of open data sources on methods for detecting internal threats to information security; construction of a model based on the application of machine learning methods; methods for sample formation and training, assessment of anomaly based on decision-making methods. The result obtained: The article presents a study of existing methods and models for detecting internal threats based on unsupervised machine learning, including multi-layer artificial neural networks. An approach to building an internal threat detection system is described and formalized, which is then applied to an existing dataset to evaluate the effectiveness of the models. The uniqueness of the proposed approach lies in the ability to detect internal threats for each record individually, as well as for each user based on the number of anomalous records. The described methods for data extraction, aggregation, and representation, formulated with the constraints of real systems in mind, were applied to a dataset of user actions over a day. Evaluations of model effectiveness were calculated for anomaly record decision-making approaches and each user. The obtained evaluations can be interpreted as a result of the models’ generalization abilities and the peculiarities of calculating anomaly values. Scientific novelty: the article presents an approach to detecting internal threats to information security that differs in the ability to detect internal threats for each record individually, as well as for each user based on the number of anomalous records.
Keywords:  internal threats, insider, threat detection, information security, anomalies, machine learning, artificial neural networks.

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