Machine Learning-Based Adaptive Synthetic Sampling Technique for Intrusion Detection
Machine Learning-Based Adaptive Synthetic Sampling Technique for Intrusion Detection
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Publisher
Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Scope and Contents
Contents
Traditional firewalls and data encryption techniques can no longer match the demands of current IoT network security due to the rising amount and variety of network threats. In order to manage IoT network risks, intrusion detection solutions have been advised. Even though machine learning (ML) helps the widely used intrusion detection techniques cu...
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Full title
Machine Learning-Based Adaptive Synthetic Sampling Technique for Intrusion Detection
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TN_cdi_doaj_primary_oai_doaj_org_article_6e8e1cddb4834d08af801e22c0c11297
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6e8e1cddb4834d08af801e22c0c11297
Other Identifiers
ISSN
2076-3417
E-ISSN
2076-3417
DOI
10.3390/app13116504
