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 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">Transport automation research</journal-id>
   <journal-title-group>
    <journal-title xml:lang="en">Transport automation research</journal-title>
    <trans-title-group xml:lang="ru">
     <trans-title>Автоматика на транспорте</trans-title>
    </trans-title-group>
   </journal-title-group>
   <issn publication-format="print">2412-9186</issn>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="publisher-id">75787</article-id>
   <article-id pub-id-type="doi">10.20295/2412-9186-2024-10-01-7-17</article-id>
   <article-categories>
    <subj-group subj-group-type="toc-heading" xml:lang="ru">
     <subject>Живучесть, надежность, безопасность</subject>
    </subj-group>
    <subj-group subj-group-type="toc-heading" xml:lang="en">
     <subject>VIABILITY, RELIABILITY, SAFETY</subject>
    </subj-group>
    <subj-group>
     <subject>Живучесть, надежность, безопасность</subject>
    </subj-group>
   </article-categories>
   <title-group>
    <article-title xml:lang="en">Fuzzy system for assessing the information security risk of intelligent water transport systems</article-title>
    <trans-title-group xml:lang="ru">
     <trans-title>НЕЧЕТКАЯ СИСТЕМА ОЦЕНКИ РИСКОВ ИНФОРМАЦИОННОЙ БЕЗОПАСНОСТИ ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ ВОДНОГО ТРАНСПОРТА</trans-title>
    </trans-title-group>
   </title-group>
   <contrib-group content-type="authors">
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Баранов</surname>
       <given-names>Леонид Аврамович</given-names>
      </name>
      <name xml:lang="en">
       <surname>Baranov</surname>
       <given-names>Leonid Avramovich</given-names>
      </name>
     </name-alternatives>
     <email>baranov.miit@gmail.com</email>
     <bio xml:lang="ru">
      <p>доктор технических наук;</p>
     </bio>
     <bio xml:lang="en">
      <p>doctor of technical sciences;</p>
     </bio>
     <xref ref-type="aff" rid="aff-1"/>
    </contrib>
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Иванова</surname>
       <given-names>Нина Дмитриевна</given-names>
      </name>
      <name xml:lang="en">
       <surname>Ivanova</surname>
       <given-names>Nina Dmitrievna</given-names>
      </name>
     </name-alternatives>
     <email>ivanovand.nina@yandex.ru</email>
     <xref ref-type="aff" rid="aff-2"/>
    </contrib>
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Михалевич</surname>
       <given-names>Игорь Феодосьевич</given-names>
      </name>
      <name xml:lang="en">
       <surname>Mihalevich</surname>
       <given-names>Igor' Feodos'evich</given-names>
      </name>
     </name-alternatives>
     <email>mif-orelf@mail.ru</email>
     <bio xml:lang="ru">
      <p>кандидат технических наук;</p>
     </bio>
     <bio xml:lang="en">
      <p>candidate of technical sciences;</p>
     </bio>
     <xref ref-type="aff" rid="aff-3"/>
    </contrib>
   </contrib-group>
   <aff-alternatives id="aff-1">
    <aff>
     <institution xml:lang="ru">Российский университет транспорта (МИИТ)</institution>
     <city>Москва</city>
     <country>Россия</country>
    </aff>
    <aff>
     <institution xml:lang="en">Russian University of Transport (MIIT)</institution>
     <city>Moscow</city>
     <country>Russian Federation</country>
    </aff>
   </aff-alternatives>
   <aff-alternatives id="aff-2">
    <aff>
     <institution xml:lang="ru">Российский университет транспорта (МИИТ)</institution>
     <city>Москва</city>
     <country>Россия</country>
    </aff>
    <aff>
     <institution xml:lang="en">Russian University of Transport (MIIT)</institution>
     <city>Moscow</city>
     <country>Russian Federation</country>
    </aff>
   </aff-alternatives>
   <aff-alternatives id="aff-3">
    <aff>
     <institution xml:lang="ru">Российский университет транспорта (МИИТ)</institution>
     <city>Москва</city>
     <country>Россия</country>
    </aff>
    <aff>
     <institution xml:lang="en">Russian University of Transport (MIIT)</institution>
     <city>Moscow</city>
     <country>Russian Federation</country>
    </aff>
   </aff-alternatives>
   <pub-date publication-format="print" date-type="pub" iso-8601-date="2024-03-17T21:59:08+03:00">
    <day>17</day>
    <month>03</month>
    <year>2024</year>
   </pub-date>
   <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2024-03-17T21:59:08+03:00">
    <day>17</day>
    <month>03</month>
    <year>2024</year>
   </pub-date>
   <volume>10</volume>
   <issue>1</issue>
   <fpage>7</fpage>
   <lpage>17</lpage>
   <history>
    <date date-type="received" iso-8601-date="2024-03-08T00:00:00+03:00">
     <day>08</day>
     <month>03</month>
     <year>2024</year>
    </date>
   </history>
   <self-uri xlink:href="https://atjournal.ru/en/nauka/article/75787/view">https://atjournal.ru/en/nauka/article/75787/view</self-uri>
   <abstract xml:lang="ru">
    <p>Интеллектуализация водного транспорта сопровождается расширением ландшафта угроз транспортной безопасности, обусловленных особенностями и слабостями внедряемых технологий, являющихся конвергенцией информационных и телекоммуникационных технологий, технологий автоматизированного и автоматического управления и искусственного интеллекта. Особенностями указанных технологий является работа с большими объемами информации. Нарушение безопасности информации, обрабатываемой в интеллектуальных системах водного транспорта (неправомерный доступ, модификация, удаление и тому подобное несанкционированное воздействие) вызывает нарушение транспортной безопасности и, как следствие, безопасности критической информационной инфраструктуры и критической инфраструктуры страны, национальной безопасности. Для конвергентных технологий, используемых в интеллектуальных транспортных системах, характерен множественный и слабо формализуемый характер проявления последствий реализации угроз. В статье представлена модель оценки рисков информационной безопасности интеллектуальных систем водного транспорта, основанная на методах теории нечетких множеств и нечеткой логики, применение которых позволяет учесть вышеизложенные особенности внедряемых технологий. Иерархическая структура модели и применение методов теории нечетких множеств и нечеткой логики позволяет адаптировать модель под различные критерии рисков, типы входных данных и уровень детализации анализа рисков. Для представленной модели разработана методика оценки рисков информационной безопасности и приведен пример расчета риска. Разработанные модель и методика предназначены для построения системы управления рисками информационной безопасности автономного судоходства, реализующей технологии гибридного (дополненного, расширенного) интеллекта, предусматривающих управляемое людьми применение искусственного интеллекта.</p>
   </abstract>
   <trans-abstract xml:lang="en">
    <p>The intellectualization of water transport is accompanied by an expansion of the landscape of threats to transport security, caused by the characteristics and weaknesses of the technologies being introduced, which are the convergence of information and telecommunication technologies, automated and automatic control technologies and artificial intelligence. The peculiarity of these technologies is working with large volumes of information. Violation of the security of information processed in intelligent systems of water transport (illegal access, modification, deletion and similar unauthorized influence) causes a violation of transport security and, as a consequence, the security of critical information infrastructure and the country’s critical infrastructure, national security. Convergent technologies used in intelligent transport systems are characterized by multiple and poorly formalized manifestations of the consequences of threats. The article presents a model for assessing the risks of information security of intelligent water transport systems, based on the methods of the theory of fuzzy sets and fuzzy logic, the use of which makes it possible to take into account the above-mentioned features of the technologies being implemented. The hierarchical structure of the model and the use of fuzzy set theory and fuzzy logic methods make it possible to adapt the model to various risk criteria, types of input data and the level of detail of risk analysis. For the presented model, a methodology for assessing information security risks has been developed and an example of risk calculation is given. The developed model and methodology are intended to build an information security risk management system for autonomous shipping, implementing technologies of hybrid (augmented, extended) intelligence, providing for the use of artificial intelligence controlled by people.</p>
   </trans-abstract>
   <kwd-group xml:lang="ru">
    <kwd>информационная безопасность</kwd>
    <kwd>водный транспорт</kwd>
    <kwd>транспортная безопасность</kwd>
    <kwd>естественный интеллект</kwd>
    <kwd>искусственный интеллект</kwd>
    <kwd>интеллектуальные системы</kwd>
    <kwd>лингвистические переменные</kwd>
    <kwd>системы агрегирования информации</kwd>
   </kwd-group>
   <kwd-group xml:lang="en">
    <kwd>transport security</kwd>
    <kwd>natural intelligence</kwd>
    <kwd>artificial intelligence</kwd>
    <kwd>intelligent systems</kwd>
    <kwd>linguistic variables</kwd>
    <kwd>information aggregation systems</kwd>
   </kwd-group>
  </article-meta>
 </front>
 <body>
  <p></p>
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