Pub Date : 2022-03-02DOI: 10.31799/1684-8853-2022-1-30-43
A. Abdullin, V. Itsykson
Introduction: Over the last years program analysis methods were widely used for software quality assurance. Different types of program analysis require various levels of program representation, analysis methods, etc. Platforms that provide utilities to implement different types of analysis on their basis become very important because they allow one to simplify the process of development. Purpose: Development of a platform for analysis of JVM programs. Results: In this paper we present Kex, a platform for building program analysis tools for JVM bytecode. Kex provides three abstraction levels. First is Kfg, which is an SSA-based control flow graph representation for bytecode-level analysis and transformation. Second is a symbolic program representation called Predicate State, which consists of first order logic predicates that represent instructions of the original program, constraints, etc. The final level is SMT integration layer for constraint solving. It currently provides an interface for interacting with three SMT solvers. Practical relevance: We have evaluated our platform by considering two prototypes. First prototype is an automatic test generation tool that has participated in SBST 2021 tool competition. Second prototype is a tool for detection of automatic library integration errors. Both prototypes have proved that Kex can be used to implement competitive and powerful program analysis tools.
{"title":"Kex: A Platform For Analysis Of JVM Programs","authors":"A. Abdullin, V. Itsykson","doi":"10.31799/1684-8853-2022-1-30-43","DOIUrl":"https://doi.org/10.31799/1684-8853-2022-1-30-43","url":null,"abstract":"Introduction: Over the last years program analysis methods were widely used for software quality assurance. Different types of program analysis require various levels of program representation, analysis methods, etc. Platforms that provide utilities to implement different types of analysis on their basis become very important because they allow one to simplify the process of development. Purpose: Development of a platform for analysis of JVM programs. Results: In this paper we present Kex, a platform for building program analysis tools for JVM bytecode. Kex provides three abstraction levels. First is Kfg, which is an SSA-based control flow graph representation for bytecode-level analysis and transformation. Second is a symbolic program representation called Predicate State, which consists of first order logic predicates that represent instructions of the original program, constraints, etc. The final level is SMT integration layer for constraint solving. It currently provides an interface for interacting with three SMT solvers. Practical relevance: We have evaluated our platform by considering two prototypes. First prototype is an automatic test generation tool that has participated in SBST 2021 tool competition. Second prototype is a tool for detection of automatic library integration errors. Both prototypes have proved that Kex can be used to implement competitive and powerful program analysis tools.","PeriodicalId":36977,"journal":{"name":"Informatsionno-Upravliaiushchie Sistemy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46266774","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}
Pub Date : 2022-03-02DOI: 10.31799/1684-8853-2022-1-54-67
V. Lipatnikov, A. Shevchenko, V. Kosolapov, Daniil Sokol
Introduction: the development of technologies in the field of information and telecommunications, as well as the unification of networks, and in particular the construction of distributed VoIP telephony networks, allow us to formulate the problem that the known methods of managing the protection of VoIP networks are not effective enough in modern conditions, since they take into account only one side of the information confrontation. Purpose: To develop a method for ensuring the information security of a VoIP telephony network, which allows to increase the probability of VoIP network security by reducing the time required for analyzing the actions of the violator, analyzing and processing risks under the influence of the violator. Results: Based on the proposed structure of an information security management system integrated into a VoIP network, a method for ensuring the information security of a VoIP telephony network under the influence of an intruder has been developed by introducing decision-making support processes in the VoIP network information security management system using intelligent intrusion detection tools distributed across segments. This method allows you to build a graph of events of the intruder's actions, on the basis of which mathematical modeling of MiTM and SPIT attacks on the VoIP telephony network is carried out. As a result of the simulation, the dependence of the successful impact on the internal and external characteristics of attacks is obtained, which is the main one of the developed software, which allows to obtain the values of the probability of security of the VoIP network from the parameters of the intruder's impact for further selection of adequate measures for managing the information security of the VoIP telephony network. The method includes the processes of analyzing the digital stream and determining the parameters of protocols and profiles of intruder attacks. Practical relevance: The developed method provides an opportunity to study issues aimed at the security of the VoIP-telephony network, which is affected by violators.
{"title":"Method for ensuring information security of a VOIP telephony network with a forecast of an intruder's intrusion strategy","authors":"V. Lipatnikov, A. Shevchenko, V. Kosolapov, Daniil Sokol","doi":"10.31799/1684-8853-2022-1-54-67","DOIUrl":"https://doi.org/10.31799/1684-8853-2022-1-54-67","url":null,"abstract":"Introduction: the development of technologies in the field of information and telecommunications, as well as the unification of networks, and in particular the construction of distributed VoIP telephony networks, allow us to formulate the problem that the known methods of managing the protection of VoIP networks are not effective enough in modern conditions, since they take into account only one side of the information confrontation. Purpose: To develop a method for ensuring the information security of a VoIP telephony network, which allows to increase the probability of VoIP network security by reducing the time required for analyzing the actions of the violator, analyzing and processing risks under the influence of the violator. Results: Based on the proposed structure of an information security management system integrated into a VoIP network, a method for ensuring the information security of a VoIP telephony network under the influence of an intruder has been developed by introducing decision-making support processes in the VoIP network information security management system using intelligent intrusion detection tools distributed across segments. This method allows you to build a graph of events of the intruder's actions, on the basis of which mathematical modeling of MiTM and SPIT attacks on the VoIP telephony network is carried out. As a result of the simulation, the dependence of the successful impact on the internal and external characteristics of attacks is obtained, which is the main one of the developed software, which allows to obtain the values of the probability of security of the VoIP network from the parameters of the intruder's impact for further selection of adequate measures for managing the information security of the VoIP telephony network. The method includes the processes of analyzing the digital stream and determining the parameters of protocols and profiles of intruder attacks. Practical relevance: The developed method provides an opportunity to study issues aimed at the security of the VoIP-telephony network, which is affected by violators.","PeriodicalId":36977,"journal":{"name":"Informatsionno-Upravliaiushchie Sistemy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44091426","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}
Pub Date : 2022-03-02DOI: 10.31799/1684-8853-2022-1-44-53
N. Moldovyan, D. Moldovyan, A. Moldovyan
Introduction: Development of practical post-quantum signature algorithms is a current challenge in the area of cryptography. Recently, several candidates on post-quantum signature schemes, in which the exponentiation operations in a hidden commutative group contained in a non-commutative algebra is used, were proposed. Search for new mechanisms of using a hidden group, while developing signature schemes resistant to quantum attacks, is of significant practical interest. Purpose: Development of a new method for designing post-quantum signature algorithms on finite non-commutative associative algebras. Results: A novel method for developing digital signature algorithms on non-commutative algebras. A new four-dimensional finite non-commutative associative algebra set over the ground field GF(p) have been proposed as algebraic support of the signature algorithms. To provide a higher performance of the algorithm, in the introduced algebra the vector multiplication is defined by a sparse basis vector multiplication table. Study of the algebra structure has shown that it can be represented as a set of commutative subalgebras of three different types, which intersect exactly in the set of scalar vectors. Using the proposed method and introduced algebra, a new post-quantum signature scheme has been designed. The introduced method is characterized in using one of the elements of the signature (e, S) in form of the four-dimensional vector S that is computed as a masked product of two exponentiated elements G and H of a hidden commutative group: S = B-1GnHmC-1, where non-permutable vectors B and C are masking multipliers; the natural numbers n and m are calculated depending on the signed document M and public key. The pair composes a minimum generator systems of the hidden group. The signature verification equation has the form R = (Y1SZ1)e(Y2SZ2)e2, where pairwise non-permutable vectors Y1, Z1, Y2, and Z2 are element of the public key and natural number e that is computed depending on the value M and the vector R. Practical relevance: Due to sufficiently small size of public key and signature and high, the developed digital signature scheme represents interest as a practical post-quantum signature algorithm. The introduced method is very attractive to develop a post-quantum digital signature standard.
{"title":"A Novel Method for Developing Post-quantum Digital Signature Algorithms on Non-commutative Associative Algebras","authors":"N. Moldovyan, D. Moldovyan, A. Moldovyan","doi":"10.31799/1684-8853-2022-1-44-53","DOIUrl":"https://doi.org/10.31799/1684-8853-2022-1-44-53","url":null,"abstract":"Introduction: Development of practical post-quantum signature algorithms is a current challenge in the area of cryptography. Recently, several candidates on post-quantum signature schemes, in which the exponentiation operations in a hidden commutative group contained in a non-commutative algebra is used, were proposed. Search for new mechanisms of using a hidden group, while developing signature schemes resistant to quantum attacks, is of significant practical interest. Purpose: Development of a new method for designing post-quantum signature algorithms on finite non-commutative associative algebras. Results: A novel method for developing digital signature algorithms on non-commutative algebras. A new four-dimensional finite non-commutative associative algebra set over the ground field GF(p) have been proposed as algebraic support of the signature algorithms. To provide a higher performance of the algorithm, in the introduced algebra the vector multiplication is defined by a sparse basis vector multiplication table. Study of the algebra structure has shown that it can be represented as a set of commutative subalgebras of three different types, which intersect exactly in the set of scalar vectors. Using the proposed method and introduced algebra, a new post-quantum signature scheme has been designed. The introduced method is characterized in using one of the elements of the signature (e, S) in form of the four-dimensional vector S that is computed as a masked product of two exponentiated elements G and H of a hidden commutative group: S = B-1GnHmC-1, where non-permutable vectors B and C are masking multipliers; the natural numbers n and m are calculated depending on the signed document M and public key. The pair composes a minimum generator systems of the hidden group. The signature verification equation has the form R = (Y1SZ1)e(Y2SZ2)e2, where pairwise non-permutable vectors Y1, Z1, Y2, and Z2 are element of the public key and natural number e that is computed depending on the value M and the vector R. Practical relevance: Due to sufficiently small size of public key and signature and high, the developed digital signature scheme represents interest as a practical post-quantum signature algorithm. The introduced method is very attractive to develop a post-quantum digital signature standard.","PeriodicalId":36977,"journal":{"name":"Informatsionno-Upravliaiushchie Sistemy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41769878","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}
Pub Date : 2022-03-02DOI: 10.31799/1684-8853-2022-1-19-29
V. Gryzunov
Introduction: Distributed in space-time Networks: IIoT and IoT, fog and edge computing tend to penetrate into all spheres of human activity. Enterprises, government, law enforcement agencies, etc. depend on the quality of those technologies. Purpose: To determine the composition of the Network that provides the required uptime probability. Methods: According to the concept of structural and functional synthesis, a distributed Network is presented as an unstable queuing system in which servicing devices are connected and disconnected at an arbitrary point in time. A simulation model of the Network has been built. Results: The state of the Network depends on the number of devices and tasks, their performance and lifetimes. The model does not use these quantities themselves, but their ratios. The values of the uptime probability of the Network are calculated for all possible combinations of ratios. The confidence interval has been calculated with a confidence level of 0.95. From the data obtained, it is clear: 1) what should be the minimum composition of the Network in order to provide the required probability; 2) what probability the current composition of the Network can provide; 3) what flow of tasks is admissible in order to solve tasks with the required probability. It is shown that the dependence of the mean tasks residence time on the Network on the composition of the Network has two inflection points. Using information about these points, the Network Management System forms pools of devices or increases the number of devices. Discussion: It is assumed that the Net has a fully connected structure. Consequently, for practical application, it is necessary: to expand the model with an adjacency matrix describing the connections between nodes, and hence the paths of propagation of tasks over the Network or consider that each node is a relay and is capable of transmitting the task to any other node on the Network. Overhead costs arising from this are taken into account by adjusting the original data. Practical relevance: The results allow minimizing costs in the design and operation of distributed systems, maximizing the likelihood of system uptime under given constraints for resource.
{"title":"Model of a distributed information system solving tasks with the required probability","authors":"V. Gryzunov","doi":"10.31799/1684-8853-2022-1-19-29","DOIUrl":"https://doi.org/10.31799/1684-8853-2022-1-19-29","url":null,"abstract":"Introduction: Distributed in space-time Networks: IIoT and IoT, fog and edge computing tend to penetrate into all spheres of human activity. Enterprises, government, law enforcement agencies, etc. depend on the quality of those technologies. Purpose: To determine the composition of the Network that provides the required uptime probability. Methods: According to the concept of structural and functional synthesis, a distributed Network is presented as an unstable queuing system in which servicing devices are connected and disconnected at an arbitrary point in time. A simulation model of the Network has been built. Results: The state of the Network depends on the number of devices and tasks, their performance and lifetimes. The model does not use these quantities themselves, but their ratios. The values of the uptime probability of the Network are calculated for all possible combinations of ratios. The confidence interval has been calculated with a confidence level of 0.95. From the data obtained, it is clear: 1) what should be the minimum composition of the Network in order to provide the required probability; 2) what probability the current composition of the Network can provide; 3) what flow of tasks is admissible in order to solve tasks with the required probability. It is shown that the dependence of the mean tasks residence time on the Network on the composition of the Network has two inflection points. Using information about these points, the Network Management System forms pools of devices or increases the number of devices. Discussion: It is assumed that the Net has a fully connected structure. Consequently, for practical application, it is necessary: to expand the model with an adjacency matrix describing the connections between nodes, and hence the paths of propagation of tasks over the Network or consider that each node is a relay and is capable of transmitting the task to any other node on the Network. Overhead costs arising from this are taken into account by adjusting the original data. Practical relevance: The results allow minimizing costs in the design and operation of distributed systems, maximizing the likelihood of system uptime under given constraints for resource.","PeriodicalId":36977,"journal":{"name":"Informatsionno-Upravliaiushchie Sistemy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44828906","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}
Pub Date : 2022-03-02DOI: 10.31799/1684-8853-2022-1-2-7
N. Balonin, M. Sergeev
Introduction: Cretan matrices – orthogonal matrices, consisting of the elements 1 and –b (real number), are an ideal object for the visual application of finite-dimensional mathematics. These matrices include, in particular, the Hadamard matrices and, with the expansion of the number of elements, the conference matrices. The most convenient research apparatus is to use field theory and multiplicative Galois groups, which is especially important for new types of Cretan matrices. Purpose: To study the symmetries of the Cretan matrices and to investigate two new types of matrices of odd and even orders, distinguished by symmetries, respectively, which differ significantly from the previously known Mersenne, Euler and Fermat matrices. Results: Formulas for levels are given and symmetries of new Cretan matrices: Odin bicycles (with a border) of orders 4t – 1 and 4t – 3 and shadow matrices of orders 4t – 2 and 4t – 4 are described. For odd character sizes equal to prime numbers and powers of primes, the existence of matrix symmetries of special types, doubly symmetric, consisting of skew-symmetric (with respect to the signs of elements) and symmetric cyclic blocks, is proved. It is shown that the previously distinguished Cretan matrices are their special case: Mersenne matrices of orders 4t – 1 and Euler matrices of orders 4t – 2 existing in the absence of symmetry for all selected orders without exception. Practical relevance: Оrthogonal sequences and methods of their effective finding by the theory of finite fields and groups are of direct practical importance for the problems of noise-immune coding, compression and masking of video information.
{"title":"Odin and Shadow Cretan matrices accompanying primes and their powers","authors":"N. Balonin, M. Sergeev","doi":"10.31799/1684-8853-2022-1-2-7","DOIUrl":"https://doi.org/10.31799/1684-8853-2022-1-2-7","url":null,"abstract":"Introduction: Cretan matrices – orthogonal matrices, consisting of the elements 1 and –b (real number), are an ideal object for the visual application of finite-dimensional mathematics. These matrices include, in particular, the Hadamard matrices and, with the expansion of the number of elements, the conference matrices. The most convenient research apparatus is to use field theory and multiplicative Galois groups, which is especially important for new types of Cretan matrices. Purpose: To study the symmetries of the Cretan matrices and to investigate two new types of matrices of odd and even orders, distinguished by symmetries, respectively, which differ significantly from the previously known Mersenne, Euler and Fermat matrices. Results: Formulas for levels are given and symmetries of new Cretan matrices: Odin bicycles (with a border) of orders 4t – 1 and 4t – 3 and shadow matrices of orders 4t – 2 and 4t – 4 are described. For odd character sizes equal to prime numbers and powers of primes, the existence of matrix symmetries of special types, doubly symmetric, consisting of skew-symmetric (with respect to the signs of elements) and symmetric cyclic blocks, is proved. It is shown that the previously distinguished Cretan matrices are their special case: Mersenne matrices of orders 4t – 1 and Euler matrices of orders 4t – 2 existing in the absence of symmetry for all selected orders without exception. Practical relevance: Оrthogonal sequences and methods of their effective finding by the theory of finite fields and groups are of direct practical importance for the problems of noise-immune coding, compression and masking of video information.","PeriodicalId":36977,"journal":{"name":"Informatsionno-Upravliaiushchie Sistemy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42583159","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}
Pub Date : 2022-03-02DOI: 10.31799/1684-8853-2022-1-8-18
A. Branitskiy, Yash Sharma, Igor Kotenko, E. Fedorchenko, A. Krasov, I. Ushakov
Introduction: diagnosing mental illness is a complex process that includes conducting dialogue conversations, analyzing the behavior of the subject and passing specialized tests. The successful solution of this problem can be influenced by both the lack of knowledge and experience of the psychologist, and the presence of contradictory or incomplete initial data on the part of the patient. To eliminate this drawback, expert-based or intelligent systems are being developed. Purpose: development of a technique for determining the mental state of social network users. Results: using machine learning methods, a technique has been developed designed to determine the type of a mental state of social network users. The novelty of the proposed technique is in the usage of a two-step text preprocessing procedure and the construction of several sets of features which describe the emotional mood of social network users at the level of the messages published by them. As the initial data, we have used text messages of users of the social network Reddit. There are three stages in the technique: 1) data collection, 2) data preprocessing, 3) post labeling and feature construction. To assess the functioning of a software tool built on the basis of this technique, four indicators were used: accuracy, precision, recall, and F-measure. The best results are demonstrated with a One-vs-Rest ensemble using linear support vector machines as basic solvers. Practical relevance: the investigation results can be used in the construction of auxiliary systems that are aimed at supporting decision-making by psychologists in determining mental disorders.
引言：诊断精神疾病是一个复杂的过程，包括进行对话、分析受试者的行为和通过专业测试。这个问题的成功解决可能受到心理学家缺乏知识和经验，以及患者存在矛盾或不完整的初始数据的影响。为了消除这一缺点，正在开发基于专家的或智能的系统。目的：开发一种确定社交网络用户心理状态的技术。结果：使用机器学习方法，开发了一种技术，用于确定社交网络用户的心理状态类型。所提出的技术的新颖之处在于使用了两步文本预处理程序，并构建了几组特征，这些特征在社交网络用户发布的消息级别上描述了他们的情绪。作为初始数据，我们使用了社交网络Reddit用户的短信。该技术分为三个阶段：1）数据收集，2）数据预处理，3）后标记和特征构建。为了评估基于该技术构建的软件工具的功能，使用了四个指标：准确性、精密度、召回率和F-measure。最佳结果通过使用线性支持向量机作为基本解算器的One vs Rest集成进行了演示。实际相关性：调查结果可用于构建辅助系统，旨在支持心理学家在确定精神障碍时的决策。
{"title":"Determination of the mental state of users of the social network Reddit based on machine learning methods","authors":"A. Branitskiy, Yash Sharma, Igor Kotenko, E. Fedorchenko, A. Krasov, I. Ushakov","doi":"10.31799/1684-8853-2022-1-8-18","DOIUrl":"https://doi.org/10.31799/1684-8853-2022-1-8-18","url":null,"abstract":"Introduction: diagnosing mental illness is a complex process that includes conducting dialogue conversations, analyzing the behavior of the subject and passing specialized tests. The successful solution of this problem can be influenced by both the lack of knowledge and experience of the psychologist, and the presence of contradictory or incomplete initial data on the part of the patient. To eliminate this drawback, expert-based or intelligent systems are being developed. Purpose: development of a technique for determining the mental state of social network users. Results: using machine learning methods, a technique has been developed designed to determine the type of a mental state of social network users. The novelty of the proposed technique is in the usage of a two-step text preprocessing procedure and the construction of several sets of features which describe the emotional mood of social network users at the level of the messages published by them. As the initial data, we have used text messages of users of the social network Reddit. There are three stages in the technique: 1) data collection, 2) data preprocessing, 3) post labeling and feature construction. To assess the functioning of a software tool built on the basis of this technique, four indicators were used: accuracy, precision, recall, and F-measure. The best results are demonstrated with a One-vs-Rest ensemble using linear support vector machines as basic solvers. Practical relevance: the investigation results can be used in the construction of auxiliary systems that are aimed at supporting decision-making by psychologists in determining mental disorders.","PeriodicalId":36977,"journal":{"name":"Informatsionno-Upravliaiushchie Sistemy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42832098","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}
Pub Date : 2021-12-16DOI: 10.31799/1684-8853-2021-6-2-9
N. Vassiliev, V. Duzhin, A. Kuzmin
Introduction: The Robinson — Schensted — Knuth (RSK) algorithm transforms a sequence of elements of a linearly ordered set into a pair of Young tableaux P, Q of the same shape. This transformation is based on the process of bumping and inserting elements in tableau P according to special rules. The trajectory formed by all the boxes of the tableau P shifted in the RSK algorithm is called the bumping route. D. Romik and P. Śniady in 2016 obtained an explicit formula for the limit shape of the bumping route, which is determined by its first element. However, the rate of convergence of the bumping routes to the limit shape has not been previously investigated either theoretically or by numerical experiments. Purpose: Carrying out computer experiments to study the dynamics of the bumping routes produced by the RSK algorithm on Young tableaux as their sizes increase. Calculation of statistical means and variances of deviations of bumping routes from their limit shapes in the L2 metric for various values fed to the input of the RSK algorithm. Results: A series of computer experiments have been carried out on Young tableaux, consisting of up to 10 million boxes. We used 300 tableaux of each size. Different input values (0.1, 0.3, 0.5, 0.7, 0.9) were added to each such tableau using the RSK algorithm, and the deviations of the bumping routes built from these values from the corresponding limit shapes were calculated. The graphs of the statistical mean values and variances of these deviations were produced. It is noticed that the deviations decrease in proportion to the fourth root of the tableau size n. An approximation of the dependence of the mean values of deviations on n was obtained using the least squares method.
{"title":"On the convergence of bumping routes to their limit shapes in the RSK algorithm: numerical experiments","authors":"N. Vassiliev, V. Duzhin, A. Kuzmin","doi":"10.31799/1684-8853-2021-6-2-9","DOIUrl":"https://doi.org/10.31799/1684-8853-2021-6-2-9","url":null,"abstract":"Introduction: The Robinson — Schensted — Knuth (RSK) algorithm transforms a sequence of elements of a linearly ordered set into a pair of Young tableaux P, Q of the same shape. This transformation is based on the process of bumping and inserting elements in tableau P according to special rules. The trajectory formed by all the boxes of the tableau P shifted in the RSK algorithm is called the bumping route. D. Romik and P. Śniady in 2016 obtained an explicit formula for the limit shape of the bumping route, which is determined by its first element. However, the rate of convergence of the bumping routes to the limit shape has not been previously investigated either theoretically or by numerical experiments. Purpose: Carrying out computer experiments to study the dynamics of the bumping routes produced by the RSK algorithm on Young tableaux as their sizes increase. Calculation of statistical means and variances of deviations of bumping routes from their limit shapes in the L2 metric for various values fed to the input of the RSK algorithm. Results: A series of computer experiments have been carried out on Young tableaux, consisting of up to 10 million boxes. We used 300 tableaux of each size. Different input values (0.1, 0.3, 0.5, 0.7, 0.9) were added to each such tableau using the RSK algorithm, and the deviations of the bumping routes built from these values from the corresponding limit shapes were calculated. The graphs of the statistical mean values and variances of these deviations were produced. It is noticed that the deviations decrease in proportion to the fourth root of the tableau size n. An approximation of the dependence of the mean values of deviations on n was obtained using the least squares method.","PeriodicalId":36977,"journal":{"name":"Informatsionno-Upravliaiushchie Sistemy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45768928","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}
Pub Date : 2021-12-16DOI: 10.31799/1684-8853-2021-6-10-20
D. Ryumin, I. Kagirov, A. Axyonov, Alexey Karpov
Introduction: Currently, the recognition of gestures and sign languages is one of the most intensively developing areas in computer vision and applied linguistics. The results of current investigations are applied in a wide range of areas, from sign language translation to gesture-based interfaces. In that regard, various systems and methods for the analysis of gestural data are being developed. Purpose: A detailed review of methods and a comparative analysis of current approaches in automatic recognition of gestures and sign languages. Results: The main gesture recognition problems are the following: detection of articulators (mainly hands), pose estimation and segmentation of gestures in the flow of speech. The authors conclude that the use of two-stream convolutional and recurrent neural network architectures is generally promising for efficient extraction and processing of spatial and temporal features, thus solving the problem of dynamic gestures and coarticulations. This solution, however, heavily depends on the quality and availability of data sets. Practical relevance: This review can be considered a contribution to the study of rapidly developing sign language recognition, irrespective to particular natural sign languages. The results of the work can be used in the development of software systems for automatic gesture and sign language recognition.
{"title":"Analytical review of models and methods for automatic recognition of gestures and sign languages","authors":"D. Ryumin, I. Kagirov, A. Axyonov, Alexey Karpov","doi":"10.31799/1684-8853-2021-6-10-20","DOIUrl":"https://doi.org/10.31799/1684-8853-2021-6-10-20","url":null,"abstract":"Introduction: Currently, the recognition of gestures and sign languages is one of the most intensively developing areas in computer vision and applied linguistics. The results of current investigations are applied in a wide range of areas, from sign language translation to gesture-based interfaces. In that regard, various systems and methods for the analysis of gestural data are being developed. Purpose: A detailed review of methods and a comparative analysis of current approaches in automatic recognition of gestures and sign languages. Results: The main gesture recognition problems are the following: detection of articulators (mainly hands), pose estimation and segmentation of gestures in the flow of speech. The authors conclude that the use of two-stream convolutional and recurrent neural network architectures is generally promising for efficient extraction and processing of spatial and temporal features, thus solving the problem of dynamic gestures and coarticulations. This solution, however, heavily depends on the quality and availability of data sets. Practical relevance: This review can be considered a contribution to the study of rapidly developing sign language recognition, irrespective to particular natural sign languages. The results of the work can be used in the development of software systems for automatic gesture and sign language recognition.","PeriodicalId":36977,"journal":{"name":"Informatsionno-Upravliaiushchie Sistemy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43392439","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}
Pub Date : 2021-12-16DOI: 10.31799/1684-8853-2021-6-42-52
T. Tatarnikova, P. Bogdanov
Introduction: The growing amount of digital data generated, among others, by smart devices of the Internet of Things makes it important to study the application of machine learning methods to the detection of network traffic anomalies, namely the presence of network attacks. Purpose: To propose a unified approach to detecting attacks at different levels of IoT network architecture, based on machine learning methods. Results: It was shown that at the wireless sensor network level, attack detection is associated with the detection of anomalous behavior of IoT devices, when the deviation of an IoT device behavior from its profile exceeds a predetermined level. Smart IoT devices are profiled on the basis of statistical characteristics, such as the intensity and duration of packet transmission, the proportion of retransmitted packets, etc. At the level of a local or global wired IoT network, data is aggregated and then analyzed using machine learning methods. Trained classifiers can become a part of a network attack detection system, making decisions about compromising a node on the fly. Models of classifiers of network attacks were experimentally selected both at the level of a wireless sensor network and at the level of a local or global wired network. The best results in terms of completeness and accuracy estimates are demonstrated by the random forest method for a wired local and/or global network and by all the considered methods for a wireless sensor network. Practical relevance: The proposed models of classifiers can be used for developing intrusion detection systems in IoT networks.
{"title":"Intrusion detection in internet of things networks based on machine learning methods","authors":"T. Tatarnikova, P. Bogdanov","doi":"10.31799/1684-8853-2021-6-42-52","DOIUrl":"https://doi.org/10.31799/1684-8853-2021-6-42-52","url":null,"abstract":"Introduction: The growing amount of digital data generated, among others, by smart devices of the Internet of Things makes it important to study the application of machine learning methods to the detection of network traffic anomalies, namely the presence of network attacks. Purpose: To propose a unified approach to detecting attacks at different levels of IoT network architecture, based on machine learning methods. Results: It was shown that at the wireless sensor network level, attack detection is associated with the detection of anomalous behavior of IoT devices, when the deviation of an IoT device behavior from its profile exceeds a predetermined level. Smart IoT devices are profiled on the basis of statistical characteristics, such as the intensity and duration of packet transmission, the proportion of retransmitted packets, etc. At the level of a local or global wired IoT network, data is aggregated and then analyzed using machine learning methods. Trained classifiers can become a part of a network attack detection system, making decisions about compromising a node on the fly. Models of classifiers of network attacks were experimentally selected both at the level of a wireless sensor network and at the level of a local or global wired network. The best results in terms of completeness and accuracy estimates are demonstrated by the random forest method for a wired local and/or global network and by all the considered methods for a wireless sensor network. Practical relevance: The proposed models of classifiers can be used for developing intrusion detection systems in IoT networks.","PeriodicalId":36977,"journal":{"name":"Informatsionno-Upravliaiushchie Sistemy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44176883","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}
Pub Date : 2021-12-16DOI: 10.31799/1684-8853-2021-6-31-41
D. Tomchin, Maria Sitchikhina, M. Ananyevskiy, T. Sventsitskaya, A. Fradkov
Introduction: The COVID-19 pandemic which began in 2020 and has taken more than five million lives has become a threat to the very existence of mankind. Therefore, predicting the spread of COVID-19 in each individual country is a very urgent task. The complexity of its solution is due to the requirement for fast processing of large amounts of data and the fact that the data are mostly inaccurate and do not have the statistical properties necessary for the successful application of statistical methods. Therefore, it seems important to develop simple forecasting methods based on classical simple models of epidemiology which are only weakly sensitive to data inaccuracies. It is also important to demonstrate the feasibility of the approach in relation to the incidence data in Russia. Purpose: Obtaining forecast data based on classical simple models of epidemics, namely SIR and SEIR. Methods: For discrete versions of SIR and SEIR models, it is proposed to estimate the parameters of the models using a reduced version of the least squares method, and apply a scenario approach to the forecasting. The simplicity and a small number of parameters are the advantages of SIR and SEIR models, which is very important in the context of a lack of numerical input data and structural incompleteness of the models. Results: A forecast of the spread of COVID-19 in Russia has been built based on published data on the incidence from March 10 to April 20, 2020, and then, selectively, according to October 2020 data and October 2021 data. The results of the comparison between SIR and SEIR forecasts are presented. The same method was used to construct and present forecasts based on morbidity data in the fall of 2020 and in the fall of 2021 for Russia and for St. Petersburg. To set the parameters of the models which are difficult to determine from the official data, a scenario approach is used: the dynamics of the epidemic is analyzed for several possible values of the parameters. Practical relevance: The results obtained show that the proposed method predicts well the time of the onset of the peak incidence, despite the inaccuracy of the initial data.
{"title":"Prediction of COVID-19 pandemic dynamics in Russia based on simple mathematical models of epidemics","authors":"D. Tomchin, Maria Sitchikhina, M. Ananyevskiy, T. Sventsitskaya, A. Fradkov","doi":"10.31799/1684-8853-2021-6-31-41","DOIUrl":"https://doi.org/10.31799/1684-8853-2021-6-31-41","url":null,"abstract":"Introduction: The COVID-19 pandemic which began in 2020 and has taken more than five million lives has become a threat to the very existence of mankind. Therefore, predicting the spread of COVID-19 in each individual country is a very urgent task. The complexity of its solution is due to the requirement for fast processing of large amounts of data and the fact that the data are mostly inaccurate and do not have the statistical properties necessary for the successful application of statistical methods. Therefore, it seems important to develop simple forecasting methods based on classical simple models of epidemiology which are only weakly sensitive to data inaccuracies. It is also important to demonstrate the feasibility of the approach in relation to the incidence data in Russia. Purpose: Obtaining forecast data based on classical simple models of epidemics, namely SIR and SEIR. Methods: For discrete versions of SIR and SEIR models, it is proposed to estimate the parameters of the models using a reduced version of the least squares method, and apply a scenario approach to the forecasting. The simplicity and a small number of parameters are the advantages of SIR and SEIR models, which is very important in the context of a lack of numerical input data and structural incompleteness of the models. Results: A forecast of the spread of COVID-19 in Russia has been built based on published data on the incidence from March 10 to April 20, 2020, and then, selectively, according to October 2020 data and October 2021 data. The results of the comparison between SIR and SEIR forecasts are presented. The same method was used to construct and present forecasts based on morbidity data in the fall of 2020 and in the fall of 2021 for Russia and for St. Petersburg. To set the parameters of the models which are difficult to determine from the official data, a scenario approach is used: the dynamics of the epidemic is analyzed for several possible values of the parameters. Practical relevance: The results obtained show that the proposed method predicts well the time of the onset of the peak incidence, despite the inaccuracy of the initial data.","PeriodicalId":36977,"journal":{"name":"Informatsionno-Upravliaiushchie Sistemy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46764784","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}
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