<?xml version="1.0" encoding="utf-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "https://jats.nlm.nih.gov/publishing/1.3/JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xml:lang="en">
  <front>
    <journal-meta>
      <journal-title-group>
        <journal-title>Computing, Telecommunication and Control</journal-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Информатика, телекоммуникации и управление</trans-title>
        </trans-title-group>
      </journal-title-group>
      <issn pub-type="epub">2687-0517</issn>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">3</article-id>
      <article-id pub-id-type="doi">10.5862/JCSTCS.217-222.3</article-id>
      <title-group>
        <article-title>Applying Mapreduce and Network Traffic Analysis to Control Access to Information Resources</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Применение технологии MapReduce для контроля доступа к информационным ресурсам в корпоративных сетях</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Laboshin</surname>
            <given-names>Leonid</given-names>
          </name>
          <email>laboshin@ya.ru</email>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Lukashin</surname>
            <given-names>Aleksey</given-names>
          </name>
          <email>lukash@neva.ru</email>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Vladimir</surname>
            <given-names>S.</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <email>vlad@neva.ru</email>
        </contrib>
      </contrib-group>
      <aff id="aff1">Peter the Great St.Petersburg Polytechnic University</aff>
      <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2015-04-10">
        <day>10</day>
        <month>04</month>
        <year>2015</year>
      </pub-date>
      <issue>2</issue>
      <issue-id pub-id-type="publisher-id">217</issue-id>
      <issue-part>3</issue-part>
      <fpage>34</fpage>
      <lpage>40</lpage>
      <abstract xml:lang="en">
        <p>Nowadays information security is an important issue. Network traffic analysis is widely used by Internet Service Providers to evaluate network performance, to collect statistics and to detect vulnerabilities. To analyze traffic traces collected from a large network it is required a computer system where both storage and computing resources can be easily scaled out to handle and process multi-Terabyte files. Cloud computing platforms and cluster file systems could provide resizable compute and storage capacity. The MapReduce programming model developed by Google in 2004 allows processing huge amounts of data in distributed manner by defining the map and reduce functions. The given paper proposes a cloud-computing framework based on a MapReduce approach for fast internet traffic analytics.</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>deep packet inspection</kwd>
        <kwd>Big Data</kwd>
        <kwd>MapReduce</kwd>
        <kwd>Hadoop</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
