Cross ML for Io(H)T Network Traffic Classification: A New Approach Towards Standardization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00382129" target="_blank" >RIV/68407700:21230/24:00382129 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/CSNet64211.2024.10851757" target="_blank" >https://doi.org/10.1109/CSNet64211.2024.10851757</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CSNet64211.2024.10851757" target="_blank" >10.1109/CSNet64211.2024.10851757</a>
Alternative languages
Result language
angličtina
Original language name
Cross ML for Io(H)T Network Traffic Classification: A New Approach Towards Standardization
Original language description
The rapid proliferation of the Internet of Things (IoT) underscores the need for robust network security, especially in sectors like healthcare. While numerous datasets support cyber-attack detection in the IoT space, there remains a challenge due to the limited availability of publicly accessible data specific to certain sectors, like healthcare. This study delves into Cross-Machine Learning (Cross-ML), a novel approach to leveraging data from multiple sources to enhance Machine Learning (ML)-based Network Intrusion Detection Systems (NIDS).
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
8th Cyber Security in Networking Conference
ISBN
9798331534103
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
282-288
Publisher name
IEEE Industrial Electronic Society
Place of publication
Vienna
Event location
Paríž
Event date
Dec 4, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001445789900047