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Evolutionary fuzzy rules for intrusion detection in wireless sensor networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F21%3A10247282" target="_blank" >RIV/61989100:27240/21:10247282 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007%2F978-3-030-57796-4_15" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-57796-4_15</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-57796-4_15" target="_blank" >10.1007/978-3-030-57796-4_15</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Evolutionary fuzzy rules for intrusion detection in wireless sensor networks

  • Original language description

    Next-generation digital services and applications often rely on large numbers of devices connected to a common communication backbone. The security of such massively distributed systems is a major issue and advanced methods to improve their ability to detect and counter cybernetic attacks are needed. Evolutionary algorithms can automatically evolve and optimize sophisticated intrusion detection models, suitable for different applications. In this work, a hybrid evolutionary-fuzzy classification and regression algorithm is used to evolve detectors for several types of intrusions in a wireless sensor network. The ability of genetic programming and differential evolution to construct and optimize intrusion detectors for wireless sensor networks is evaluated on a recent intrusion detection data set capturing malicious activity in a wireless sensor network. (C) Springer Nature Switzerland AG 2021.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10200 - Computer and information sciences

Result continuities

  • Project

    <a href="/en/project/TN01000024" target="_blank" >TN01000024: National Competence Center - Cybernetics and Artificial Intelligence</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Advances in Intelligent Systems and Computing. Volume 1263

  • ISBN

    978-3-030-57795-7

  • ISSN

    2194-5357

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    149-160

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Victoria

  • Event date

    Aug 31, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article