Intrusion Detection System (IDS) of multiclassification IoT by using pipelining and an efficient machine learning
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Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The Internet of Things (IoT) has quickly advanced and been incorporated into many different fields. With the use of IoT technology, gadgets can receive, process, and send data automatically. IoT has been rapidly accepted in many important fields since it makes life easier and increases service quality, yet it still faces significant privacy and security problems. An Intrusion Detection System (IDS) could be implemented as a security feature to protect IoT networks from a variety of cyberattacks. This study suggests using IDS to defend against a wide range of cyberattacks on IoT systems. The suggested approach makes use of the Multi-layer Perceptron (MLP) as well as Extra Trees (ExT) as efficient algorithms of classification. Also, the study uses the pipeline to put together several cross-validated phases while selecting various parameters to increase the detection rate. One dataset is utilized for evaluating and analyzing the performance outcomes so as to validate the efficiency of the suggested IDS approach. The evaluation findings show that the suggested IDS methods may greatly increase detection performance results concerning accuracy rate, precision, F1-score, and recall while also improving detection efficiency.
Açıklama
Anahtar Kelimeler
Cybersecurity, Internet of Things (IoT), Intrusion detection system (IDS), Machine learning, Network security, Pipeline
Kaynak
9th International Conference on Engineering and Emerging Technology, ICEET 2023
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Hazim, L. R., Jasim, A. A., Ata, O., Ilyas, M. (2023). Intrusion Detection System (IDS) of multiclassification IoT by using pipelining and an efficient machine learning. 9th International Conference on Engineering and Emerging Technology, ICEET 2023. 10.1109/ICEET60227.2023.10525915
