D. P. Zegzhda, A. F. Suprun, V. G. Anisimov, A. V. Tebekin, E. G. Anisimov
{"title":"Methodological Approach to Construct Models for Predicting Indicators of Properties of Information Security Systems","authors":"D. P. Zegzhda, A. F. Suprun, V. G. Anisimov, A. V. Tebekin, E. G. Anisimov","doi":"10.3103/S0146411623080357","DOIUrl":"10.3103/S0146411623080357","url":null,"abstract":"<p>A methodological approach to construct models for predicting indicators of properties of information security systems at evolutionary stages of development is proposed. The approach is based on the idea of the development of information security systems as a process of change in the acceptable range of indicators characterizing their properties. It is assumed that the number of resources spent on improving each property is greater the closer the current value of the indicator characterizing this property is to the maximum possible value for the information security system under consideration. This circumstance is taken into account by reducing the relative rates of improvement in indicators as their values approach the maximum possible value.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"881 - 885"},"PeriodicalIF":0.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140001809","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":"Hybrid Method for the Detection of Evasion Attacks Aimed at Machine Learning Systems","authors":"M. O. Kalinin, A. F. Suprun, O. D. Ivanova","doi":"10.3103/S0146411623080072","DOIUrl":"10.3103/S0146411623080072","url":null,"abstract":"<p>The existing methods for the detection of evasion attacks in machine learning systems are analyzed. An experimental comparison of the methods is carried out. The uncertainty method is universal; however, in this method, it is difficult to determine such uncertainty boundaries for adversarial examples that would enable the precise identification of evasion attacks, which would result in lower efficiency parameters with respect to the skip gradient method (SGM) attack, maps of significance (MS) attack, and boundary attack (BA) compared to the other methods. A new hybrid method representing the two-stage input data verification complemented with preliminary processing is developed. In the new method, the uncertainty boundary for adversarial objects has become distinguishable and quickly computable. The hybrid method makes it possible to detect out-of-distribution (OOD) evasion attacks with a precision of not less than 80%, and SGM, MS, and BA attacks with a precision of 93%.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"983 - 988"},"PeriodicalIF":0.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140001801","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}
V. M. Krundyshev, G. A. Markov, M. O. Kalinin, P. V. Semyanov, A. G. Busygin
{"title":"Cyberattack Detection in the Industrial Internet of Things Based on the Computation Model of Hierarchical Temporal Memory","authors":"V. M. Krundyshev, G. A. Markov, M. O. Kalinin, P. V. Semyanov, A. G. Busygin","doi":"10.3103/S0146411623080114","DOIUrl":"10.3103/S0146411623080114","url":null,"abstract":"<p>This study considers the problem of detecting network anomalies caused by computer attacks in the networks of the industrial Internet of things. To detect anomalies, a new method is proposed, built using a hierarchical temporal memory (HTM) computation model based on the neocortex model. An experimental study of the developed method of detecting computer attacks based on the HTM model showed the superiority of the developed solution over the LSTM analog. The developed prototype of the anomaly detection system provides continuous training on unlabeled data sets in real time, takes into account the current network context, and applies the accumulated experience by supporting the memory mechanism.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"1040 - 1046"},"PeriodicalIF":0.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888817","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":"Application of Machine Learning Methods to the Problem of Searching for a Region of Interest for Biometric Identification Based on the Pattern of Palm Veins","authors":"A. I. Almuhamedov, V. S. Kolomoitcev","doi":"10.3103/S0146411623080023","DOIUrl":"10.3103/S0146411623080023","url":null,"abstract":"<p>This paper discusses the problem of searching for a region of interest for biometric identification based on the pattern of palm veins. An image segmentation method is proposed based on the use of convolutional neural networks (CNNs) to search for a region of interest. The operation of this method is compared with methods that use the features of a binarized image, and in particular, with the method of searching for the local minima and searching for the minimum threshold value.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"1126 - 1134"},"PeriodicalIF":0.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888821","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":"Defense against Adversarial Attacks on Image Recognition Systems Using an Autoencoder","authors":"V. V. Platonov, N. M. Grigorjeva","doi":"10.3103/S0146411623080230","DOIUrl":"10.3103/S0146411623080230","url":null,"abstract":"<p>Adversarial attacks on artificial neural network systems for image recognition are considered. To improve the security of image recognition systems against adversarial attacks (evasion attacks), the use of autoencoders is proposed. Various attacks are considered and software prototypes of autoencoders of full-link and convolutional architectures are developed as means of defense against evasion attacks. The possibility of using developed prototypes as a basis for designing autoencoders more complex architectures is substantiated.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"989 - 995"},"PeriodicalIF":0.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888886","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":"Finding Enumerators for Generalized (L, G)-Code","authors":"I. K. Noskov, S. V. Bezzateev","doi":"10.3103/S0146411623080187","DOIUrl":"10.3103/S0146411623080187","url":null,"abstract":"<p>The algorithm for finding the enumerators of degree 2 and higher for the generalized (<i>L</i>, <i>G</i>)‑code is presented. This algorithm makes it possible to enhance the rate of finding enumerators as distinct from the exhaustive search algorithm. It can be used to construct a modern variant of the McEliece cryptosystem. The presented solution is based on using the representation of the Galois field element via the function containing the coefficients of a smaller field. In addition, the results of comparison of the modern McEliece cryptosystem constructed based on the Goppa codes and generalized (<i>L</i>, <i>G</i>)-codes are presented.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"922 - 927"},"PeriodicalIF":0.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142414877","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 Decompiled Program Code Using Abstract Syntax Trees","authors":"N. A. Gribkov, T. D. Ovasapyan, D. A. Moskvin","doi":"10.3103/S0146411623080060","DOIUrl":"10.3103/S0146411623080060","url":null,"abstract":"<p>This article proposes a method for preprocessing fragments of binary program codes for subsequent detection of their similarity using machine learning methods. The method is based on the analysis of pseudocode obtained as a result of decompiling fragments of binary codes. The analysis is performed using attributed abstract syntax trees (AASTs). As part of the study, testing and comparative analysis of the effectiveness of the developed method are carried out. This method makes it possible to increase the efficiency of detecting functionally similar fragments of program code, compared to analogs, by using the semantic context of vertices in abstract syntax trees.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"958 - 967"},"PeriodicalIF":0.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888807","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":"Decimation of M Sequences As a Way of Obtaining Primitive Polynomials","authors":"D. V. Kushnir, S. N. Shemyakin","doi":"10.3103/S0146411623080138","DOIUrl":"10.3103/S0146411623080138","url":null,"abstract":"<p>One approach to obtain a cryptographically strong encryption gamma is to use linear-feedback shift registers defined by primitive polynomials. The ability to quickly select the appropriate polynomial can provide the required degree of security of the stream cipher. Currently, primitive polynomials for sufficiently large degrees are known, but usually these are so-called sparse polynomials. To increase the correlational stability, it is necessary to be able to quickly generate new primitive polynomials of the given degrees, which is the focus of this study.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"928 - 932"},"PeriodicalIF":0.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140001692","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":"Method for Detecting Manipulation Attacks on Recommender Systems with Collaborative Filtering","authors":"A. D. Dakhnovich, D. S. Zagalsky, R. S. Solovey","doi":"10.3103/S0146411623080047","DOIUrl":"10.3103/S0146411623080047","url":null,"abstract":"<p>The security of recommendation systems with collaborative filtering from manipulation attacks is considered. The most common types of attacks are analyzed and identified. A modified method for detecting manipulation attacks on recommendation systems with collaborative filtering is proposed. Experimental testing and a comparison of the effectiveness of the modified method with other current methods are carried out.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"868 - 874"},"PeriodicalIF":0.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142414910","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 Cryptographic Protection of the Bitcoin Core Cryptographic Wallet","authors":"P. V. Semyanov, S. V. Grezina","doi":"10.3103/S0146411623080278","DOIUrl":"10.3103/S0146411623080278","url":null,"abstract":"<p>This article discusses the security of implementing encryption for the Bitcoin Core cryptocurrency wallet. Particular attention is paid to aspects of the practical use of cryptographic algorithms when encrypting the wallet.dat file with a password. Practical resistance to brute-force attacks using parallel computing on GPUs is also considered. It is discovered that Bitcoin Core does not implement changing the encryption key for the user’s private keys. This implementation makes it possible to carry out a second attack on the wallet without knowing the new password, if it has already been compromised previously. Changes to encryption algorithms are also been proposed to make brute-force attacks more difficult on the GPU.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"914 - 921"},"PeriodicalIF":0.6,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140001683","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}