{"title":"Model of a Distributed Storage System for Crypto Wallet Private Keys","authors":"M. R. Salikhov","doi":"10.3103/S0146411624700949","DOIUrl":"10.3103/S0146411624700949","url":null,"abstract":"<p>With the development of Web3 technologies, the third generation of the Internet has become one of the most promising areas. It involves the use of decentralized, transparent, and user-oriented applications. However, many Web3 projects do not pay sufficient attention to security, which can lead to serious consequences. Even a small error in the code can make the system vulnerable, opening access to attackers. As a result, the industry faces frequent security breaches that threaten users and undermine trust in new technologies. One of the main problems with Web3 is private key management. This is a critical security aspect that is directly related to the protection of digital assets and users' personal information. The risk of losing or theft of a private key can lead to irreparable consequences, since in the case of loss there is no way to restore or reset the key. Various ways of storing the private key of a crypto wallet to ensure security are discussed. For example, the key can be split into parts and stored encrypted on hardware media, or the entire encrypted key can be stored on secure media. Quantitative data are calculated using Shamir’s scheme.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 8","pages":"1289 - 1296"},"PeriodicalIF":0.6,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Assessing the Security of Big Data Systems","authors":"M. A. Poltavtseva, V. V. Zaitseva, D. V. Ivanov","doi":"10.3103/S0146411624701025","DOIUrl":"10.3103/S0146411624701025","url":null,"abstract":"<p>This article considers the problem of assessing the security of big data systems. The authors define the main aspects of big data systems as an object of security assessment and analyze the known assessment methods, including methodologies for assessing the security of information systems (ISs). Based on the obtained results, a new evaluation method is proposed that takes into account factors such as the state of the access control system in the heterogeneous systems under consideration and the number of privileged users. A mathematical formalization of the assessment is proposed, the main stages of its implementation are described, and a test example is presented.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 8","pages":"1352 - 1364"},"PeriodicalIF":0.6,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. F. Suprun, A. Yu. Gar’kushev, A. V. Lipis, I. L. Karpova, A. A. Shalkovskaya
{"title":"Assessment of the Competence of an Intelligent Information Security Management System","authors":"A. F. Suprun, A. Yu. Gar’kushev, A. V. Lipis, I. L. Karpova, A. A. Shalkovskaya","doi":"10.3103/S0146411624701220","DOIUrl":"10.3103/S0146411624701220","url":null,"abstract":"<p>This article studies the development of tools for assessing intelligent information security (IS) management systems (MSs) at enterprises. The proposed methodology is based on a combination of methods of the entropy approach to assessing the quality of information and a priori assessment of competence in terms of the balance between the efficiency and validity of the decisions taken. The proposed mathematical model can be used for the a priori assessment of decision support systems in the field of information security.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 8","pages":"1429 - 1435"},"PeriodicalIF":0.6,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identification and Verification of Authorship Using Machine and Deep Learning Methods","authors":"T. D. Ovasapyan, E. M. Tolgorenko, E. A. Zubkov","doi":"10.3103/S0146411624700925","DOIUrl":"10.3103/S0146411624700925","url":null,"abstract":"<p>This article presents studies aimed at analyzing methods for determining and confirming the authorship of texts. Methods for transforming texts into vector representations and determining authorship through text classification are investigated. A data set is formed on which the studied methods are tested, after which conclusions are drawn about their effectiveness. Further directions for research are also proposed.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 8","pages":"1271 - 1282"},"PeriodicalIF":0.6,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Providing Information Security of Vehicular Ad Hoc Networks Using the Early Detection of Malicious Nodes","authors":"E. Yu. Pavlenko, M. A. Pakhomov","doi":"10.3103/S0146411624700986","DOIUrl":"10.3103/S0146411624700986","url":null,"abstract":"<p>The peculiarities of vehicular ad hoc networks (VANETs) are considered. An approach to provide information security of VANETs is proposed; its distinctive feature lies in the early detection of malicious activity of network participants. For its detection at an early stage, the parameters of the ad hoc vehicular network are represented as a time series, and the prediction of their future values and anomaly detection are carried out using machine learning methods. The proposed approach allows improving the security of intelligent transport systems.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 8","pages":"1318 - 1325"},"PeriodicalIF":0.6,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Protecting Machine Learning Models from Training Data Set Extraction","authors":"M. O. Kalinin, A. A. Muryleva, V. V. Platonov","doi":"10.3103/S0146411624700871","DOIUrl":"10.3103/S0146411624700871","url":null,"abstract":"<p>The problem of protecting machine learning models from the threat of data privacy violation implementing membership inference in training data sets is considered. A method of protective noising of the training set is proposed. It is experimentally shown that Gaussian noising of training data with a scale of 0.2 is the simplest and most effective way to protect machine learning models from membership inference in the training set. In comparison with alternatives, this method is easy to implement, universal in relation to types of models, and allows reducing the effectiveness of membership inference to 26 percentage points.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 8","pages":"1234 - 1241"},"PeriodicalIF":0.6,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Threat Model for Decentralized Messaging Systems","authors":"E. M. Orel, I. A. Anoshkin, D. A. Moskvin","doi":"10.3103/S0146411624700767","DOIUrl":"10.3103/S0146411624700767","url":null,"abstract":"<p>A model of information security threats for messaging systems with a decentralized nodal structure is presented. Information flows are considered, and a diagram of information states in the process of the interaction of network devices within the framework of a decentralized messaging system is developed. The presented security threats correspond to the classification of the Data Bank of Information Security Threats of the Federal Service for Technical and Export Control, and are also divided into levels of the reference model of open systems’ interaction. For each of the threats listed, the methods of their implementation are considered and the possible source of the threat is described.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 8","pages":"1139 - 1146"},"PeriodicalIF":0.6,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the Application of the Calculus of Positively Constructed Formulas for the Study of Controlled Discrete-Event Systems","authors":"A. V. Davydov, A. A. Larionov, N. V. Nagul","doi":"10.3103/S0146411624700445","DOIUrl":"10.3103/S0146411624700445","url":null,"abstract":"<p>The article is devoted to the development of an approach to solving the main problems of the theory of supervisory control of logical discrete-event systems (DES), based on their representation in the form of positively constructed formulas (PCF). We consider logical DESs in automata form, understood as generators of some regular languages. The PCF language is a complete first-order language, the formulas of which have a regular structure of alternating type quantifiers and do not contain a negation operator in the syntax. It was previously proven that any formula of the classical first-order predicate calculus can be represented as a PCF. PCFs have a visual tree representation and a natural question-and-answer procedure for searching for an inference using a single inference rule. It is shown how the PCF calculus, developed in the 1990s to solve some problems of control of dynamic systems, makes it possible to solve basic problems of the theory of supervisory control, such as checking the criteria for the existence of supervisory control, automatically modifying restrictions on the behavior of the controlled system, and implementing a supervisor. Due to some features of the PCF calculus, it is possible to use a non-monotonic inference. It is demonstrated how the presented PCF-based method allows for additional event processing during inference. The Bootfrost software system, or the so-called prover, designed to refute the obtained PCFs is also presented, and the features of its implementation are briefly described. As an illustrative example, we consider the problem of controlling an autonomous mobile robot.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 7","pages":"1042 - 1062"},"PeriodicalIF":0.6,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Algorithms for Asymptotic and Numerical Modeling of Oscillatory Modes in the Simplest Ring of Generators with Asymmetric Nonlinearity","authors":"S. D. Glyzin, E. A. Marushkina","doi":"10.3103/S0146411624700305","DOIUrl":"10.3103/S0146411624700305","url":null,"abstract":"<p>A system of three ring-coupled generators with asymmetric nonlinearity and special nonlinear coupling is considered. The investigated system simulates an electrical circuit of three identical generators. Each generator is an oscillatory circuit with a nonlinear element. The current–voltage characteristic of this element has the <i>S</i>-shape. The nonlinear coupling between the generators is organized in such a way that it has a transmission coefficient close to one in the forward direction and close to zero in the reverse direction. First, the problem of finding the solutions that bifurcate from equilibrium states is investigated by asymptotic methods. Then, the original system is studied by numerical methods. The dependence of the dynamics of the system on the degree of asymmetry of cubic nonlinearity, which describes the characteristic of the nonlinear element, is analyzed.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 7","pages":"853 - 860"},"PeriodicalIF":0.6,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. S. Lagutina, K. V. Lagutina, A. M. Brederman, N. N. Kasatkina
{"title":"Text Classification by CEFR Levels Using Machine Learning Methods and the BERT Language Model","authors":"N. S. Lagutina, K. V. Lagutina, A. M. Brederman, N. N. Kasatkina","doi":"10.3103/S0146411624700329","DOIUrl":"10.3103/S0146411624700329","url":null,"abstract":"<p>This paper presents a study of the problem of automatic classification of short coherent texts (essays) in English according to the levels of the international CEFR scale. Determining the level of text in a natural language is an important component of assessing a student’s knowledge, including checking open tasks in e-learning systems. To solve this problem, vector text models are considered based on the stylometric numerical features of the character, word, and sentence structure levels. The obtained vectors are classified by the standard machine learning classifiers. This article presents the results of the three most successful ones: Support Vector Classifier, Stochastic Gradient Descent Classifier, and LogisticRegression. Precision, comprehensiveness, and the F-measure served as the quality measures. Two open text corpora, CEFR Levelled English Texts and BEA-2019, are chosen for the experiments. The best classification results for six CEFR levels and sublevels from A1 to C2 are shown by the Support Vector Classifier with an F-score of 67% for the CEFR Levelled English Texts. This approach is compared with the application of the BERT language model (six different variants). The best model, bert-base-cased, provided an F-score value of 69%. The analysis of classification errors shows that most of them are between neighboring levels, which is quite understandable from the point of view of the domain. In addition, the quality of classification strongly depends on the text corpus, which demonstrates a significant difference in F-scores during the application of the same text models for different corpora. In general, the results obtained show the effectiveness of automatic text level determination and the possibility of its practical application.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 7","pages":"869 - 878"},"PeriodicalIF":0.6,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}