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Бабалова, Ирина Филипповна

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Институт интеллектуальных кибернетических систем
Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.
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Бабалова
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Ирина Филипповна
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2020 - 20214
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  • Уменьшенное изображение
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    Development of a System of Anonymizing Mobile Calls
    (2020) Borushnova, A. V.; Ivanov, N. S.; Babalova, I. F.; Бабалова, Ирина Филипповна
    © 2020 IEEE.Voice over Internet Protocol (VoIP) is a technology that allows people to use the Internet, rather than a traditional telephone network. VoIP is becoming more and more popular due to its significant advantages. VoIP telephony has become the most developed and frequently used cellular service. It also created new threats to caller's privacy. Due to the high degree of interest in ensuring anonymization of calls in the GSM network. Previous research on the development of algorithms to increase anonymization in IP-telephony and their implementation. In this work, we developed a new mechanism for achieving anonymity in the Global System for Mobile Communications (GSM - Global System for Mobile Communications). The lowest probability of anonymity disclosure in this algorithm is achieved by redirecting calls from one mobile operator to another. In addition, GPSS-Studio implements a model for redirecting incoming calls using multi-channel modeling. Probabilistic-temporal characteristics of the distribution of incoming calls to specific nodes.
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    Classification of Websites Based on the Content and Features of Sites in Onion Space
    (2020) Korolev, D.; Frolov, A.; Babalova, I.; Королев, Денис Вячеславович; Бабалова, Ирина Филипповна
    © 2020 IEEE.This paper describes a method for classifying onion sites. According to the results of the research, the most spread model of site in onion space is built. To create such a model, a specially trained neural network is used. The classification of neural network is based on five different categories such as using authentication system, corporate email, readable URL, feedback and type of onion-site. The statistics of the most spread types of websites in Dark Net are given.
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    Automation Check Vulnerabilities of Access Points Based on 802.11 Protocol
    (2020) Subbotin, D.; Babalova, I.; Bazanov, V.; Ivanov, N.; Бабалова, Ирина Филипповна
    © 2020 IEEE.Wi-Fi technology has a huge distribution around the world. There are a large number of devices that in one way or another work with different versions of the 802.11 protocol. However, this technology has a large number of different vulnerabilities. Many of them can be solved in the production of Wi-Fi modules. But not all manufacturers produce modules with fixed vulnerabilities. Therefore, the objective of this article is to create a product that can automatically check the stability of a wi-fi module to DoS attacks.
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    Formation and Analysis of the Patent Database on Computer Technologies
    (2021) Urkaewa, K. D.; Babalova, I. F.; Zareshin, S. V.; Бабалова, Ирина Филипповна
    © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.This article will consider the method of creating a patent database based on information provided by various patent offices, and its subsequent analysis by displaying the information of interest at the user’s request. The assessment of existing solutions and their shortcomings is carried out. The features of existing databases are taken into account. The categories to search for patents are selected according to the International Patent Classification (IPC). During the experiment, we proposed an optimal algorithm for obtaining data and uploading it to our own database. Patent data was also collected from existing databases (for example, Google Patents), which in turn draw data from open government departments. The possibility of processing the obtained data by filtering out unnecessary information and analysis of HTML pages of patents for certain parameters, is investigated. The paper considers the method of creating a database and filling it with the found information, as well as the output ordered by special criteria, carried out using the free relational database management system MySQL [1], also specialized libraries for Python 3.8. In the last part, some clippings from the obtained statistics and conclusions based on them are presented.