{"title":"Trust-Model-Based Method for Protecting Global Models in Federated Learning Systems","authors":"V. M. Krundyshev, V. K. Cheskidov, M. O. Kalinin","doi":"10.3103/S0146411625700762","DOIUrl":"10.3103/S0146411625700762","url":null,"abstract":"<p>The problem of ensuring the security of a global computational model in federated learning systems is considered. A method is proposed that is based on data verification using a trusted group of nodes and ensures that only correct updates are taken into account during the global model aggregation process. It is experimentally demonstrated that the developed method ensures accurate identification and isolation of adversaries implementing label-flipping and noise-injection threats.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 8","pages":"1242 - 1252"},"PeriodicalIF":0.5,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147341649","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":"Automated Method for Evaluating the Correctness of Distributed Algorithms Using Chaos Engineering Testing","authors":"A. D. Dakhnovich, A. A. Lyrchikov, D. A. Moskvin","doi":"10.3103/S0146411625700786","DOIUrl":"10.3103/S0146411625700786","url":null,"abstract":"<p>This article presents a method for evaluating the correctness of distributed algorithms using chaos engineering methods to improve the efficiency of their testing. Modern research studies are analyzed in the field of testing distributed systems, such as federated learning systems for large language models (LLMs) and chaos engineering. The existing testing methods and tools based on chaos engineering are analyzed and their shortcomings are identified. As a result, a method for evaluating the correctness of distributed systems through testing using chaos engineering is developed, and vulnerability testing is conducted in open source projects, followed by a comparison with the existing methods. The obtained results confirm the effectiveness of the proposed method.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 8","pages":"1260 - 1269"},"PeriodicalIF":0.5,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147341650","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":"Automated Software Security Analysis for the Android OS","authors":"E. Yu. Pavlenko, I. A. Anoshkin","doi":"10.3103/S0146411625700798","DOIUrl":"10.3103/S0146411625700798","url":null,"abstract":"<p>This article presents methods for the automated security analysis of Android applications, which can be used to search for cryptographic vulnerabilities, vulnerabilities in third-party software components, authentication, and authorization, as well as to identify the storage and transmission of sensitive information in clear text. The accuracy of searching for the given types of vulnerabilities using automated vulnerability search tools and a software prototype is analyzed.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 8","pages":"1270 - 1277"},"PeriodicalIF":0.5,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147341758","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":"Artificial Immunization in Hierarchical and Peer-to-Peer Networks to Protect Against Cyber Threats","authors":"E. Yu. Pavlenko, N. N. Samarin","doi":"10.3103/S0146411625701093","DOIUrl":"10.3103/S0146411625701093","url":null,"abstract":"<p>Immunization approaches for cyber-physical systems based on hierarchical and peer-to-peer network topologies are described. A systematic analysis of existing immunization methods based on graph theory is carried out, together with theoretical formalization and experimentation. The approach demonstrates sufficient effectiveness of artificial immunization using global strategies for cyber-physical systems based on a hierarchical network infrastructure.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 8","pages":"1519 - 1526"},"PeriodicalIF":0.5,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147341522","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":"Countering Illegitimate Activations of a Smart Voice Assistant","authors":"M. A. Poltavtseva, A. V. Bolokan, P. V. Semyanov","doi":"10.3103/S014641162570097X","DOIUrl":"10.3103/S014641162570097X","url":null,"abstract":"<p>This study focuses on ensuring the security of smart voice assistants against the most pressing threats by reducing the number of illegitimate activations. An analysis of threats to smart voice assistants (SVAs) and a list of the functional capabilities of voice assistants are presented. The goal is to reduce the number of illegitimate activations of SVAs. The architecture and operating method of a proprietary security module that reduces the number of illegitimate activations are presented. The developed module is tested and the results are positive.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 8","pages":"1415 - 1425"},"PeriodicalIF":0.5,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147341523","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":"Detecting the Spread of False News Content Using Machine Learning","authors":"D. S. Lavrova, A. A. Zyryanova, A. A. Lyrchikov","doi":"10.3103/S0146411625700890","DOIUrl":"10.3103/S0146411625700890","url":null,"abstract":"<p>The problem of detecting unreliable news content is studied and a solution based on machine learning methods is proposed. Modern approaches used to assess the reliability of textual and multimedia content are analyzed, with promising approaches identified and adapted to the Russian-language media space. A combined method for detecting fake news is proposed, based on the joint analysis of textual and multimedia information, as well as the characteristics of content dissemination. Testing the proposed method confirmed its effectiveness and applicability for the automated detection of unreliable news content in real-world information systems.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 8","pages":"1345 - 1356"},"PeriodicalIF":0.5,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147341586","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. N. Shenets, E. B. Aleksandrova, A. S. Konoplev, N. V. Gololobov
{"title":"Key Pre-Distribution Technique Using Shamir’s Secret Sharing Scheme","authors":"N. N. Shenets, E. B. Aleksandrova, A. S. Konoplev, N. V. Gololobov","doi":"10.3103/S0146411625700956","DOIUrl":"10.3103/S0146411625700956","url":null,"abstract":"<p>In [1], two new approaches to key pre-distribution based on an ideal additive homomorphic secret sharing scheme (SSS) are proposed. However, it has not been possible to prove their security against insider attacks in the general case. In this study, a simple method for distributing shares, corresponding to the first approach in [1], is proposed and analyzed using Shamir’s SSS. The problem considered is the distribution of 2<i>n</i> shares among <i>n</i> participants in such a way that each participant holds two shares, and every pair of participants corresponds to a (3,4)-threshold scheme, while the overall threshold can be arbitrary. It should be noted that this is the first time such a problem is solved in the theory of secret sharing. The analysis shows that the key agreement protocol based on the proposed technique of shares pre-distribution is not resistant to insider attacks. A general necessary condition for the security of a key agreement protocol in the internal adversary model is obtained.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 8","pages":"1395 - 1402"},"PeriodicalIF":0.5,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147341590","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}
I. Yu. Zhukov, E. E. Balashova, A. P. Mandrov, N. D. Kravchenko
{"title":"Construction of a Semantic Space of Intentionalities Using Generative Pretrained Models to Solve the Problem of Spam Filtering","authors":"I. Yu. Zhukov, E. E. Balashova, A. P. Mandrov, N. D. Kravchenko","doi":"10.3103/S0146411625701032","DOIUrl":"10.3103/S0146411625701032","url":null,"abstract":"<p>One of the key elements in solving spam filtering problems is the text vectorization method. This article proposes a vectorization method based on matching text to pairs of intentionalities. A list of intentionality pairs is extracted and a synthetic dataset is generated from text utterances. A neural network is designed and trained to determine the degree to which each intentionality belongs to the textual expression provided as the input of the model. The developed method is tested on the problem of filtering spam messages using logistic regression and the Enron dataset and SMS dataset.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 8","pages":"1475 - 1483"},"PeriodicalIF":0.5,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147341592","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":"Multisignature on Isogenies of Elliptic Curves with Participant Masking and Authentication","authors":"E. B. Aleksandrova, S. O. Kostin","doi":"10.3103/S0146411625700920","DOIUrl":"10.3103/S0146411625700920","url":null,"abstract":"<p>Approaches for constructing postquantum electronic signature schemes are studied. Modern methods for improving the security of protocols based on elliptic curve isogenies are analyzed. A multisignature scheme based on the problem of finding isogenies between supersingular curves with participant authentication is proposed. The effectiveness and safety of the proposed scheme are proved.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 8","pages":"1371 - 1376"},"PeriodicalIF":0.5,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147341653","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":"Analysis of Malware Detection Methods Using Large Language Models and eBPF Technology","authors":"E. Yu. Pavlenko, M. S. Ivanov","doi":"10.3103/S0146411625700828","DOIUrl":"10.3103/S0146411625700828","url":null,"abstract":"<p>A review of malware detection software tools using Large Language Models (LLMs) and Extended Berkeley Packet Filter (eBPF) technology is provided. For each product considered, a brief description is provided, and its advantages and disadvantages are highlighted. The results of a comparative analysis of the considered tools are presented, allowing us to identify areas of research in the area under consideration that most require attention.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"59 8","pages":"1292 - 1299"},"PeriodicalIF":0.5,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147341654","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}