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Machine Learning Based IoT Intrusion Detection System: An MQTT Case Study

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00346883" target="_blank" >RIV/68407700:21230/20:00346883 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-030-64758-2_6" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-64758-2_6</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Machine Learning Based IoT Intrusion Detection System: An MQTT Case Study

  • Original language description

    The Internet of Things (IoT) is one of the main research fields in the Cybersecurity domain. This is due to (a) the increased dependency on automated device, and (b) the inadequacy of general-purpose Intrusion Detection Systems (IDS) to be deployed for special purpose networks usage. Numerous lightweight protocols are being proposed for IoT devices communication usage. One of the distinguishable IoT machine-to-machine communication protocols is Message Queuing Telemetry Transport (MQTT) protocol. However, as per the authors best knowledge, there are no available IDS datasets that include MQTT benign or attack instances and thus, no IDS experimental results available.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Selected Papers from the 12th International Networking Conference

  • ISBN

    978-3-030-64757-5

  • ISSN

    2367-3370

  • e-ISSN

    2367-3389

  • Number of pages

    12

  • Pages from-to

    73-84

  • Publisher name

    Springer International Publishing

  • Place of publication

    Cham

  • Event location

    Rhodes

  • Event date

    Sep 19, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article