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Next–Generation Intrusion Detection for IoT EVCS: Integrating CNN, LSTM, and GRU Models

Next–Generation Intrusion Detection for IoT EVCS: Integrating CNN, LSTM, and GRU Models

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6a847da0a45443ad8529efa46ad8436f

Next–Generation Intrusion Detection for IoT EVCS: Integrating CNN, LSTM, and GRU Models

About this item

Full title

Next–Generation Intrusion Detection for IoT EVCS: Integrating CNN, LSTM, and GRU Models

Publisher

Basel: MDPI AG

Journal title

Mathematics (Basel), 2024-02, Vol.12 (4), p.571

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

In the evolving landscape of Internet of Things (IoT) and Industrial IoT (IIoT) security, novel and efficient intrusion detection systems (IDSs) are paramount. In this article, we present a groundbreaking approach to intrusion detection for IoT-based electric vehicle charging stations (EVCS), integrating the robust capabilities of convolutional neu...

Alternative Titles

Full title

Next–Generation Intrusion Detection for IoT EVCS: Integrating CNN, LSTM, and GRU Models

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_6a847da0a45443ad8529efa46ad8436f

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6a847da0a45443ad8529efa46ad8436f

Other Identifiers

ISSN

2227-7390

E-ISSN

2227-7390

DOI

10.3390/math12040571

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