Vol 22, No 4 (2023)

Year: 2023
Articles: 8
URL: https://bakhtiniada.ru/2713-3192/issue/view/17104

Full Issue

Information security

Information-Theoretic Representation of Interception Network Channel Virtualization

Sinyuk A.D., Ostroumov O.A., Tarasov A.A.

Abstract

The most difficult task of secure telecommunication systems using symmetric encryption, due to the need for preliminary and resource-intensive organization of secret channels for delivering keys to network correspondents, is key management. An alternative is the generating keys methods through open communication channels. In information theory, it is shown that these methods are implemented under the condition that the channel information rate of correspondents exceeds the rate of the intruder interception channel. The search for methods that provide the informational advantage of correspondents is being updated. The goal is to determine the information-theoretical conditions for the formation of a virtual network and an interception channel, for which the best ratio of information speeds for correspondents is provided compared to the ratio of the original network and interception channel. The paper proposes an information transfer model that includes a connectivity model and an information transfer method for asymptotic lengths of code words. The model includes three correspondents and is characterized by the introduction of an ideal broadcast channel in addition to an errored broadcast channel. The model introduces a source of "noisy" information, which is transmitted over the channel with errors, so the transmission of code words using the known method of random coding is carried out over the channel without errors. For asymptotic lengths of code words, all actions of correspondents in processing and transmitting information in the model are reduced to the proposed method of transmitting information. The use of the method by correspondents within the framework of the transmission model makes it possible to simultaneously form for them a new virtual broadcast channel with information rate as in the original channel with errors, and for the intruder a new virtual broadcast interception channel with a rate lower than the information rate of the initial interception channel. The information-theoretic conditions for deterioration of the interception channel are proved in the statement. The practical significance of the results obtained lies in the possibility of using the latter to assess the information efficiency of open network key formation in the proposed information transfer model, as well as in the development of well-known scientific achievements of open key agreement. The proposed transmission model can be useful for researching key management systems and protecting information transmitted over open channels. Further research is related to the information-theoretic assessment of the network key throughput, which is the potential information-theoretic speed of network key formation.

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Informatics and Automation. 2023;22(4):721-744

721-744

(Rus)

(JATS XML)

Optimal Nonlinear Filtering of Information Impact Estimates in a Stochastic Model of Information Warfare

Polansky I.S., Loginov K.O.

Abstract

A computationally efficient algorithmic solution to the problem of optimal nonlinear filtering of information impact estimates in a generalized stochastic model of information warfare is developed in the article. The formed solution is applicable in the presence of heterogeneous rules for measuring the parameters of the information warfare model, on the basis of which a pair of systems of stochastic differential equations is formed. According to the criterion of maximum likelihood according to the determined evolution of the a posteriori conditional probability density function at a given observation interval, the evaluation of the information impact in the optimal nonlinear filtering model is performed. Taking into account the probability addition theorem, as the probability of the sum of two joint events, the density functions of which are established from the numerical solution of the corresponding robust Duncan-Mortensen-Zakai equations, finding a posteriori conditional probability density function at a given time is performed. For the first event, it is assumed that the first system of stochastic differential equations is the equation of state, and the second – is the equation of observation. For the second event, their definition is set in reverse order. The solution of the robust Duncan-Mortensen-Zakai equation is carried out in the formulation of the Galerkin spectral method when sampling the observation interval into subintervals and reducing the initial solution to a numerical recurrent study of the sequence of subtasks using the so-called Yau-Yau's algorithm, which assumes an estimate of the probability measure from the solution of the direct Kolmogorov equation with its subsequent correction by observation. To highlight the features of the algorithmic implementation of the compiled solution, an algorithm for optimal nonlinear filtering of information impact estimates in a generalized stochastic model of information confrontation when specifying the listing of the function implementing it, which is represented by a pseudocode, has been formed. To identify the preference of the compiled algorithmic solution for optimal nonlinear filtering of information impact assessments, a series of computational experiments on large-volume test samples was carried out. The result of the information impact assessment obtained by the proposed algorithm is compared with the determined solution: 1) by the average sample values from the observation models; 2) by an ensemble extended Kalman filter; 3) by a filtering algorithm involving a numerical study of the Duncan-Mortensen-Zakai equation. According to the conducted a posteriori study, quantitative indicators that establish the gain of the compiled algorithm and the limits of its applicability are highlighted.

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Informatics and Automation. 2023;22(4):745-776

745-776

(Rus)

(JATS XML)

Comparative Analysis of Rumour Detection on Social Media Using Different Classifiers

Gidwani M., Rao A.

Abstract

As the number of users on social media rise, information creation and circulation increase day after day on a massive basis. People can share their ideas and opinions on these platforms. A social media microblogging site such as Facebook or Twitter is the favoured medium for debating any important event, and information is shared immediately. It causes rumours to spread quickly and circulates inaccurate information, making people uneasy. Thus, it is essential to evaluate and confirm the level of veracity of such information. Because of the complexities of the text, automated detection of rumours in their early phases is challenging. This research employs various NLP techniques to extract information from tweets and then applies various machine learning models to determine whether the information is a rumour. The classification is performed using three classifiers such as SVC (Support Vector Classifier), Gradient Boosting, and Naive Bayes classifiers for five different events from the PHEME dataset. Some drawbacks include limited handling of imbalanced data, difficulty capturing complex linguistic patterns, lack of interpretability, difficulty handling large feature spaces, and insensitivity to word order and context by using the above classifiers. The stacking approach is used to overcome the above drawbacks in which the output of combined classifiers is an ensemble with LSTM. The performance of the models has been analyzed. The experimental findings reveal that the ensemble model obtained efficient outcomes compared to other classifiers, with an accuracy of 93.59%.

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Informatics and Automation. 2023;22(4):777-794

777-794

(Eng)

(JATS XML)

AAFNDL - An Accurate Fake Information Recognition Model Using Deep Learning for the Vietnamese Language

Hung N.V., Loi T.Q., Huong N.T., Hang T.T., Huong T.T.

Abstract

On the Internet, "fake news" is a common phenomenon that frequently disturbs society because it contains intentionally false information. The issue has been actively researched using supervised learning for automatic fake news detection. Although accuracy is increasing, it is still limited to identifying fake information through channels on social platforms. This study aims to improve the reliability of fake news detection on social networking platforms by examining news from unknown domains. Especially, information on social networks in Vietnam is difficult to detect and prevent because everyone has equal rights to use the Internet for different purposes. These individuals have access to several social media platforms. Any user can post or spread the news through online platforms. These platforms do not attempt to verify users or the content of their locations. As a result, some users try to spread fake news through these platforms to propagate against an individual, a society, an organization, or a political party. In this paper, we proposed analyzing and designing a model for fake news recognition using Deep learning (called AAFNDL). The method to do the work is: 1) First, we analyze the existing techniques such as Bidirectional Encoder Representation from Transformer (BERT); 2) We proceed to build the model for evaluation; and finally, 3) We approach some Modern techniques to apply to the model, such as the Deep Learning technique, classifier technique and so on to classify fake information. Experiments show that our method can improve by up to 8.72% compared to other methods.

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Informatics and Automation. 2023;22(4):795-825

795-825

(Eng)

(JATS XML)

Digital information telecommunication technologies

Errors Compensation Caused by Time Delay of Digital Sensors

Gaiduk A.R., Prokopenko N.N., Bugakova A.V.

Abstract

The paper is devoted to improving the accuracy of digital sensors with a time lag. The relevance of the topic is due to the widespread use of sensors of this type, which is largely due to a sharp increase in the requirements for measurement accuracy. The timeliness is associated also with the extensive application of digital technologies for information processing in control systems, communications, monitoring and many others. To eliminate the errors caused by the time delay of digital sensors, it is suggested to use an astatic high-speed corrector. The applicability of this corrector is justified by the properties of discrete-time dynamical systems. In this regard, at first, the conditions are considered under which the discrete systems are physically realizable and have a finite duration of the transient since in this latter case they are the fastest. It is also shown that in order to measure a polynomial signal of limited intensity with zero error in steady-state mode, the astatism order of the sensor must be one value greater than the degree of this signal. Based on the above conditions, the main result of the article is proved – a theorem in which the conditions for the existence of the astatic high-speed corrector are established. When this corrector is switched on at the output of the digital sensor or when its software is being corrected an upgraded sensor is formed, the error of which will be zero in steady-state mode. This is due to the fact that the corrector eliminates the error of the digital sensor caused by its time delay, which is assumed to be multiple of the sampling period. The order of the corrector as a system is determined by the integer solution of the equation obtained in the work, which relates the degree of the measured polynomial signal, the time delay of the digital sensor, the permissible overshoot of the upgraded sensor and the relative order of the desired corrector. This equation is solved for the cases, where the degree of the measured signals is not greater than one, the overshoot is equal to the frequently assigned values, and the time delay does not exceed four sampling periods. The corresponding order of the upgraded sensor is given in tabular form. This makes it possible to find the required corrector without solving the shown equation in many cases. The effectiveness of the suggested approach with respect to improving the accuracy of digital sensors is shown by a numerical example. The zero error value of the upgraded sensor is confirmed both by computer simulation and numerical calculation. The results obtained can be used in the development of high-precision digital sensors of various physical quantities.

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Informatics and Automation. 2023;22(4):826-852

826-852

(Rus)

(JATS XML)

Comparison and Retrieval of Situations in the Case-Based Reasoning System for Smart-Farm

Glukhikh I.N., Prokhoshin A.S., Glukhikh D.I.

Abstract

The trend of development of smart farms is aimed at their becoming fully autonomous, robotic enterprises. The prospects for the intellectualization of agricultural production and smart farms, in particular, today are associated with the development of technology systems used to detect, recognize complex production situations and search for effective solutions in these situations. The article presents the concept of such a decision support system on smart farms using the method of decision support based on case-based reasoning - CBR system. Its implementation requires a number of non-trivial tasks, which include, first of all, the tasks of formalizing the presentation of situations and creating methods for comparing and retrieving situations from the KB on this basis. In this study, a smart farm is presented as a complex technological object consisting of interrelated components, which are the technological subsystems of a smart farm, the products produced, the objects of the operational environment, as well as the relationships between them. To implement algorithms for situational decision-making based on precedents, a formalized representation of the situation in the form of a multivector is proposed. This allowed us to develop a number of models of the trained similarity function between situations. The conducted experiments have shown the operability of the proposed models, on the basis of which ensemble architecture of a neural network has been developed for comparing situations and selecting them from the knowledge base in decision-making processes. Of practical interest is monitoring the condition of plants by their video and photo images, which allows detecting undesirable plant conditions (diseases), which can serve as a signal to activate the process of searching for solutions in the knowledge base.

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Informatics and Automation. 2023;22(4):853-879

853-879

(Rus)

(JATS XML)

Hybrid Optimization Based on Spectrum Aware Opportunistic Routing for Cognitive Radio Ad Hoc Networks

Abdullah H.M., Kumar A., Qasem Ahmed A.A., Saeed Mosleh M.A.

Abstract

Opportunistic routing has increased the efficiency and reliability of Cognitive Radio Ad-Hoc Networks (CRAHN). Many researchers have developed opportunistic routing models, among them the Spectrum Map-empowered Opportunistic Routing (SMOR) model, which is considered a more efficient model in this field. However, there are certain limitations in SMOR, which require attention and resolution. The issue of delay and degradation of packet delivery ratio due to non-consideration of network bandwidth and throughput are addressed in this paper. In order to resolve these issues, a hybrid optimization algorithm comprising firefly optimization and grey wolf optimization algorithms are used in the basic SMOR routing model. Thus, developed Hybrid Firefly and Grey-Wolf Optimization-based SMOR (HFGWOSMOR) routing model improves the performance by high local as well as global search optimization. Initially, the relationship between the delay and throughput is analyzed and then the cooperative multipath communication is established. The proposed routing model also computes the energy values of the received signals within the bandwidth threshold and time; hence, the performance issues found in SMOR are resolved. To evaluate its efficiency, the proposed model is compared with SMOR and other existing opportunistic routing models, which show that the proposed HFGWOSMOR performs better than other models.

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Informatics and Automation. 2023;22(4):880-905

880-905

(Eng)

(JATS XML)

Integration of Heterogeneous Information Resources and Earth Remote Sensing Data in Monitoring and Management of Territorial Development

Zelentsov V.A., Pimanov I.Y., Potryasayev S.A.

Abstract

The article is devoted to the development of model-algorithmic support and software tools for automating the integration of Earth remote sensing data and other heterogeneous information resources in solving problems of monitoring and proactive management of territories development. A distinctive feature of the problem statement is the inclusion of tools for modeling the state of natural and technical objects located in the analyzed territory into the resources should be integrated. The development is based on the justification of the technology for integrating heterogeneous information resources, which includes an algorithm for choosing the type of architecture for the created automation tool complex, a method for describing the information process of integrating data and their joint processing, an algorithm for determining the best configuration of information resources when solving thematic problems, as well as a set of software and technological solutions for integration of remote sensing data with other necessary data and their joint use in modeling. As a result of research and developed algorithms application, it has been established that the most preferred type of systems’ architecture for integrating heterogeneous information resources is a service-oriented architecture. To describe the information integration process, it is proposed to use a Business Process Model and Notation. The key component of the development in terms of software and technological solutions for the integration of heterogeneous data is the proposed interaction scheme with data providers and consumers based on data abstraction layer creation. The application of the proposed solution allows you to bring heterogeneous data to a single format suitable for further processing on modeling tools. The testing carried out on specific thematic tasks of monitoring and managing the territories’ development showed the feasibility of the proposed integration technology and the developed software tools, as well as the achievement of a significant gain in the rapidness of solving thematic tasks.

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Informatics and Automation. 2023;22(4):906-940

906-940

(Rus)

(JATS XML)

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