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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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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
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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
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