Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-445-456
R. I. Battalov, A. Nikonov, M. Gayanova, V. V. Berkholts, R. Gayanov
Traffic analysis systems are widely used in monitoring the network activity of users or a specific user and restricting client access to certain types of services (VPN, HTTPS) which makes content analysis impossible. Algorithms for classifying encrypted traffic and detecting VPN traffic are proposed. Three algorithms for constructing classifiers are considered - MLP, RFT and KNN. The proposed classifier demonstrates recognition accuracy on a test sample up to 80%. The MLP, RFT and KNN algorithms had almost identical performance in all experiments. It was also found that the proposed classifiers work better when the network traffic flows are generated using short values of the time parameter (timeout). The novelty lies in the development of network traffic analysis algorithms based on a neural network, differing in the method of selection, generation and selection of features, which allows to classify the existing traffic of protected connections of selected users according to a predetermined set of categories.
{"title":"Network traffic analyzing algorithms on the basis of machine learning methods","authors":"R. I. Battalov, A. Nikonov, M. Gayanova, V. V. Berkholts, R. Gayanov","doi":"10.18287/1613-0073-2019-2416-445-456","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-445-456","url":null,"abstract":"Traffic analysis systems are widely used in monitoring the network activity of users or a specific user and restricting client access to certain types of services (VPN, HTTPS) which makes content analysis impossible. Algorithms for classifying encrypted traffic and detecting VPN traffic are proposed. Three algorithms for constructing classifiers are considered - MLP, RFT and KNN. The proposed classifier demonstrates recognition accuracy on a test sample up to 80%. The MLP, RFT and KNN algorithms had almost identical performance in all experiments. It was also found that the proposed classifiers work better when the network traffic flows are generated using short values of the time parameter (timeout). The novelty lies in the development of network traffic analysis algorithms based on a neural network, differing in the method of selection, generation and selection of features, which allows to classify the existing traffic of protected connections of selected users according to a predetermined set of categories.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"215 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75593223","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-149-157
O. Golovnin
The article describes the road, institutional and weather conditions that affect the traffic flow. I proposed a method for traffic flow profiling using a data-driven approach. The method operates with macroscopic traffic flow characteristics and detailed data of road conditions. The article presents the results of traffic flow speed and intensity profiling taking into account weather conditions. The study used road traffic and conditions data for the city of Aarhus, Denmark. The results showed that the method is effective for traffic flow forecasting due to varying road conditions.
{"title":"Data-driven profiling of traffic flow with varying road conditions","authors":"O. Golovnin","doi":"10.18287/1613-0073-2019-2416-149-157","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-149-157","url":null,"abstract":"The article describes the road, institutional and weather conditions that affect the traffic flow. I proposed a method for traffic flow profiling using a data-driven approach. The method operates with macroscopic traffic flow characteristics and detailed data of road conditions. The article presents the results of traffic flow speed and intensity profiling taking into account weather conditions. The study used road traffic and conditions data for the city of Aarhus, Denmark. The results showed that the method is effective for traffic flow forecasting due to varying road conditions.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75737871","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-477-486
A. Kirillova, V. Vasilyev, A. Nikonov, V. V. Berkholts
The problem of ensuring the information security of an automated process control system (APCS) is considered. An overview of the main regulatory documents on ensuring the safety of automated process control systems is given. For the operative solution of the tasks of ensuring information security of the automated control system of technological processes it is proposed to use an intelligent decision support system (DSS). An example of the construction and implementation of decision rules in the composition of the DSS based on the use of neurofuzzy models is considered.
{"title":"Decision support system in the task of ensuring information security of automated process control systems","authors":"A. Kirillova, V. Vasilyev, A. Nikonov, V. V. Berkholts","doi":"10.18287/1613-0073-2019-2416-477-486","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-477-486","url":null,"abstract":"The problem of ensuring the information security of an automated process control system (APCS) is considered. An overview of the main regulatory documents on ensuring the safety of automated process control systems is given. For the operative solution of the tasks of ensuring information security of the automated control system of technological processes it is proposed to use an intelligent decision support system (DSS). An example of the construction and implementation of decision rules in the composition of the DSS based on the use of neurofuzzy models is considered.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73160283","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-173-182
K. Serdyukov, T V Avdeenko
In present paper we propose an approach to automatic generation of test data set based on application of the genetic algorithm. We consider original procedure for computation of the weights of code operations used to formulate the fitness function being the sum of these weights. Terminal objective and result of fitness function selection is maximization of code coverage by generated test data set. The idea of the genetic algorithm application approach is that first we choose the most complex branches of the program code for accounting in the fitness function. After taking the branch into account its weight is reset to zero in order to ensure maximum code coverage. By adjusting the algorithm, it is possible to ensure that the automatic test data generating algorithm finds the most distant from each other parts of the program code and, thus, the higher level of code coverage is attained. We give a detailed example illustrating the work and advantages of considered approach and suppose further improvements of the method.
{"title":"Using genetic algorithm for generating optimal data sets to automatic testing the program code","authors":"K. Serdyukov, T V Avdeenko","doi":"10.18287/1613-0073-2019-2416-173-182","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-173-182","url":null,"abstract":"In present paper we propose an approach to automatic generation of test data set based on application of the genetic algorithm. We consider original procedure for computation of the weights of code operations used to formulate the fitness function being the sum of these weights. Terminal objective and result of fitness function selection is maximization of code coverage by generated test data set. The idea of the genetic algorithm application approach is that first we choose the most complex branches of the program code for accounting in the fitness function. After taking the branch into account its weight is reset to zero in order to ensure maximum code coverage. By adjusting the algorithm, it is possible to ensure that the automatic test data generating algorithm finds the most distant from each other parts of the program code and, thus, the higher level of code coverage is attained. We give a detailed example illustrating the work and advantages of considered approach and suppose further improvements of the method.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"306 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74972881","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-409-416
Oleg Surnin, P. Sitnikov, Anastasia Khorina, A. Ivaschenko, A. Stolbova, N. Ilyasova
Nowadays, the world is moving to automation. Appropriate programs for the implementation of industrial applications are developed by many companies. But is it so easy to implement systems capable of processing large amounts of information in production? Despite multiple positive results in research and development of Big Data technologies, their practical implementation and use remain challenging. At the same time most prominent trends of digital economy require Big Data analysis in various problem domains. We carried out the analysis of existing data processing works. Based on generalization of theoretical research and a number of real economy projects in this area there is proposed in this paper an architecture of a software development kit that can be used as a solid platform to build industrial applications. Was formed a basic algorithm for processing data from various sources (sensors, corporate systems, etc.). Examples are given for automobile industry with a reference of Industry 4.0 paradigm implementation in practice. The given examples are illustrated by trends graphs and by subject area ontology of the automotive industry.
{"title":"Industrial application of big data services in digital economy","authors":"Oleg Surnin, P. Sitnikov, Anastasia Khorina, A. Ivaschenko, A. Stolbova, N. Ilyasova","doi":"10.18287/1613-0073-2019-2416-409-416","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-409-416","url":null,"abstract":"Nowadays, the world is moving to automation. Appropriate programs for the implementation of industrial applications are developed by many companies. But is it so easy to implement systems capable of processing large amounts of information in production? Despite multiple positive results in research and development of Big Data technologies, their practical implementation and use remain challenging. At the same time most prominent trends of digital economy require Big Data analysis in various problem domains. We carried out the analysis of existing data processing works. Based on generalization of theoretical research and a number of real economy projects in this area there is proposed in this paper an architecture of a software development kit that can be used as a solid platform to build industrial applications. Was formed a basic algorithm for processing data from various sources (sensors, corporate systems, etc.). Examples are given for automobile industry with a reference of Industry 4.0 paradigm implementation in practice. The given examples are illustrated by trends graphs and by subject area ontology of the automotive industry.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76033474","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-297-301
L. Lebedev, A. O. Shakhlan
In this paper, we consider the solution of the problem of increasing the speed of the algorithm for hyperspectral images (HSI) compression, based on recognition methods. Two methods are proposed to reduce the computational complexity of a lossy compression algorithm. The first method is based on the use of compression results obtained with other parameters, including those of the recognition method. The second method is based on adaptive partitioning of hyperspectral image pixels into clusters and calculating the estimates of similarity only with the templates of one of the subsets. Theoretical and practical estimates of the increase in the speed of the compression algorithm are obtained.
{"title":"Optimization of computational complexity of lossy compression algorithms for hyperspectral images","authors":"L. Lebedev, A. O. Shakhlan","doi":"10.18287/1613-0073-2019-2391-297-301","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-297-301","url":null,"abstract":"In this paper, we consider the solution of the problem of increasing the speed of the algorithm for hyperspectral images (HSI) compression, based on recognition methods. Two methods are proposed to reduce the computational complexity of a lossy compression algorithm. The first method is based on the use of compression results obtained with other parameters, including those of the recognition method. The second method is based on adaptive partitioning of hyperspectral image pixels into clusters and calculating the estimates of similarity only with the templates of one of the subsets. Theoretical and practical estimates of the increase in the speed of the compression algorithm are obtained.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82143822","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-79-85
N. Andriyanov, M. N. Sluzhivyi
When describing a real image using a mathematical model, the problem of model parameters identification is of importance. In this case the identification itself is easier to perform when a particular type of model is known. In other words, if there is a number of models characterized by different properties, then if there is a correspondence with the type of suitable images, then the model to be used can be determined in advance. Therefore, in this paper, we do not consider the criteria for model selection, but perform the identification of parameters for autoregressive models, including those with multiple roots of characteristic equations. This is due to the fact that the effectiveness of identification is verified by the images generated by this model. However, even using this approach where the model is known, one must first determine the order of the model. In this regard, on the basis of YuleWalker equations, an algorithm for determining the order of the model is investigated, and the optimal parameters of the model are also found. In this case the proposed algorithm can be used when processing real images.
{"title":"Solution for the problem of the parameters identification for autoregressions with multiple roots of characteristic equations","authors":"N. Andriyanov, M. N. Sluzhivyi","doi":"10.18287/1613-0073-2019-2391-79-85","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-79-85","url":null,"abstract":"When describing a real image using a mathematical model, the problem of model parameters identification is of importance. In this case the identification itself is easier to perform when a particular type of model is known. In other words, if there is a number of models characterized by different properties, then if there is a correspondence with the type of suitable images, then the model to be used can be determined in advance. Therefore, in this paper, we do not consider the criteria for model selection, but perform the identification of parameters for autoregressive models, including those with multiple roots of characteristic equations. This is due to the fact that the effectiveness of identification is verified by the images generated by this model. However, even using this approach where the model is known, one must first determine the order of the model. In this regard, on the basis of YuleWalker equations, an algorithm for determining the order of the model is investigated, and the optimal parameters of the model are also found. In this case the proposed algorithm can be used when processing real images.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"32 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89537449","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-534-541
M. P. Osipov, O. A. Chekodaev
The paper presents methods for optimizing the process of visualization of the urban environment model based on the characteristics of its presentation. Various approaches are described which provide a reduction in computational complexity in visualizing threedimensional models that can optimize the display of their geometry and the amount of video memory used. Methods are considered that allow optimizing both the scene as a whole and its individual components.
{"title":"Optimization of the process of 3D visualization of the model of urban environment objects generated on the basis of the attributive information from a digital map","authors":"M. P. Osipov, O. A. Chekodaev","doi":"10.18287/1613-0073-2019-2416-534-541","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-534-541","url":null,"abstract":"The paper presents methods for optimizing the process of visualization of the urban environment model based on the characteristics of its presentation. Various approaches are described which provide a reduction in computational complexity in visualizing threedimensional models that can optimize the display of their geometry and the amount of video memory used. Methods are considered that allow optimizing both the scene as a whole and its individual components.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"243 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91435226","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-104-110
A. A. Kolpakov, Y. Kropotov
This paper discusses the structure of the devices and their defining formulas used for local approximation using power-algebraic polynomials when the observed data are nown exactly. A multichannel system for processing discrete sequences is considered. On the basis of the considered system the research of acceleration of calculations in the system from specialized computational modules is carried out. The carried out researches have shown, that the developed model of multichannel data processing system allows to reduce essentially time for data processing.
{"title":"Local approximation of discrete processes by interpolation polynomials","authors":"A. A. Kolpakov, Y. Kropotov","doi":"10.18287/1613-0073-2019-2416-104-110","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-104-110","url":null,"abstract":"This paper discusses the structure of the devices and their defining formulas used for local approximation using power-algebraic polynomials when the observed data are nown exactly. A multichannel system for processing discrete sequences is considered. On the basis of the considered system the research of acceleration of calculations in the system from specialized computational modules is carried out. The carried out researches have shown, that the developed model of multichannel data processing system allows to reduce essentially time for data processing.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88731211","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 : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-121-127
Y. Podgornova, S. S. Sadykov
Breast cancer is the most common disease of the current century in the female population of the world. The main task of the research of most scientists is the detection of this pathology at an early stage (the tumor size is less than 7 mm) when a woman can still be helped. An indicator of this disease is the presence of small-point microcalcifications, located in groups within or in the immediate circle of the tumor. Microcalcification is a small-point character at cancer, reminding grains of sand of irregular shape which sizes are from 100 to 600 microns. The probability of breast cancer increases with the increase in the number of microcalcifications per unit area. So, the probability of cancer is 80% if more than 15 microcalcifications on 1 sq. cm. The microcalcifications are often the only sign of breast cancer, therefore, their detection even in the absence of a tumor node could be a harbinger to cancer. Image segmentation is one way to identify microcalcifications. The conducted research allowed us to choose the optimal segmentation algorithms of mammograms to highlight areas of microcalcifications for further analysis of their groups, sizes, and so on.
{"title":"Comparative analysis of segmentation algorithms for the allocation of microcalcifications on mammograms","authors":"Y. Podgornova, S. S. Sadykov","doi":"10.18287/1613-0073-2019-2391-121-127","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-121-127","url":null,"abstract":"Breast cancer is the most common disease of the current century in the female population of the world. The main task of the research of most scientists is the detection of this pathology at an early stage (the tumor size is less than 7 mm) when a woman can still be helped. An indicator of this disease is the presence of small-point microcalcifications, located in groups within or in the immediate circle of the tumor. Microcalcification is a small-point character at cancer, reminding grains of sand of irregular shape which sizes are from 100 to 600 microns. The probability of breast cancer increases with the increase in the number of microcalcifications per unit area. So, the probability of cancer is 80% if more than 15 microcalcifications on 1 sq. cm. The microcalcifications are often the only sign of breast cancer, therefore, their detection even in the absence of a tumor node could be a harbinger to cancer. Image segmentation is one way to identify microcalcifications. The conducted research allowed us to choose the optimal segmentation algorithms of mammograms to highlight areas of microcalcifications for further analysis of their groups, sizes, and so on.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87160744","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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