HIGH TECH IN EARTH SPACE RESEARCH

Filtering unwanted applications of Internet resources for information security purposes

Sheluhin O.I., Smychek M.A., Simonyan A.G.

The paper shows the actual task of controlling access to Internet resources, which has important practical importance: blocking access to illegal, extremist, antisocial information, preventing the leakage of confidential information via the Internet, etc. To solve such problems, methods of machine learning are widely used.

Traditional methods for classifying network traffic, based on both port numbers and information load, rely on the direct study of network packets. If there is a complete and tagged training dataset, it is advisable to build a classifier using Machine Learning (ML) and Data Mining technologies, which turned out to be the most effective. It is impossible to create an "ideal" classifier, until the problems existing in this field are solved. First of all, this is the absence of a general, representative set of input data that could become standard for research in this field. Most of well-known studies devoted to the problem of traffic classification, omit the fundamental requirement to determine the unknown type of traffic.

The aim of the paper is to investigate the efficiency of algorithms for classifying network traffic applications in the presence of background traffic.

The novelty of the presented solution is the analysis of the following application groups: Web-protocols for browsing web-sites - http, https; ftp-protocol for transferring ftp files; mail-protocols for sending e-mail - SMTP, POP3, IMAP; p2p-protocols of applications that use peer-to-peer networks for file transfer using machine learning algorithms: C4.5; Random Forests; Support Vector Machine (SVM); Bagging and Adaptive Boost in the presence of unclassified (background) traffic.

It is shown that the quality of classification in the presence of background traffic is reduced for all classification algorithms under consideration. However, since the algorithms C4.5, Random Forests, Bagging, and AdaBoost are built on the use of decision trees - one in the case of C4.5 or the set, their characteristics remain sufficiently high and differ insignificantly.

The subject of published articles on the nomenclature of specialties

2.2.15 Systems, networks and telecommunications (technical sciences)

2.3.1 System analysis, management and processing of information (technical sciences)

2.3.5 Mathematical and software of computing systems, complexes and computer networks (technical sciences)

2.3.6 Methods and information protection systems, information security (technical sciences)

2.5.13 Design, design and production of aircraft (technical sciences)

2.5.16 Dynamics, ballistics, the movement of aircraft (technical sciences)

Editorial board

Bobrowsky V.I.
(Ph.D., Associate Professor, Head of Department of "INTELTEH")

Borisov V.V.
(Ph.D., Professor, Actual Member of the Academy of Military Sciences, Professor, Department of Computer Science of MPEI)

Budko P.A.
(Ph.D., Professor, Department of Technical communication and automation in S.M. Budjonny Military Academy of the Signal Corps)

Budnikov S.A.
(Ph.D., associate professor, Actual Member of the Academy of Education Informatization, Head of the automated control systems Department in Russian Air Force Military Educational and Scientific Center “Air Force Academy named after Professor N.E. Zhukovsky and Y.A. Gagarin”)

Verhova G.V.
(Ph.D., Professor, Head of Department of Automation communication companies In the Bonch-Bruevich Saint Petersburg State University of Telecommunications)

Goncharevsky V.S.
(Ph.D., Professor, Honored Worker of Science and Technology of the Russian Federation, Professor of technologies and technical support and maintenance of the automated control systems in Military Space Academy of A.F. Mozhaysky)

Komashinskiy V.I.
(Ph.D., Professor, professor of processing and transmission discrete messages in the Bonch-Bruevich Saint Petersburg State University of Telecommunications)

Kirpanev A.V.
(Ph.D., Associate Professor, Head of JSC "Scientific Production Enterprise "Radar MMS")

Kurnosov V.I.
(Ph.D., Professor, Academician of Academy of Sciences of the Arctic, Academician of the International Academy of Informatization, International Academy of defense, security, law and order, corresponding member of the Academy of Natural Sciences, Senior Researcher" Open Joint Stock Company "Scientific Research Institute "Rubin")

Manuilov Y.S.
(Ph.D., Professor, Department of automated control systems space complexes in Military Space Academy of A.F. Mozhaysky)

Morozov A.V.
(Ph.D., Professor, Actual Member of the Academy of Military Sciences, Head of the Department of automated command and control systems in Military Аcademy of troops of antiaircraft defense)

Moshak N.N.
(Ph.D., Associate Professor, head of the department of "INTELTEH")

Prorok V.Y.
(Ph.D., Professor, professor of automatic control systems in Military Space Academy of A.F. Mozhaysky)

Semenov S.S.
(Ph.D., associate professor, professor of technical communication and automation in S.M. Budjonny Military Academy of the Signal Corps)

Sinicyn E.A.
(Ph.D., Professor, Head of the Research Department of JSC "The All-Russian research institute of radio equipment")

Shatrakov Y.G.
(Ph.D., Professor, Honored Worker of Science, Scientific Secretary of JSC "The All-Russian research institute of radio equipment")