A Study on Network Intrusion Detection System

Author(s)	Mohammed Kaif, Prajwal P, Laxmi V
Country	India
Abstract	An extensive overview of network intrusion detection systems (NIDS) is provided in the abstract, emphasizing the importance of these systems for protecting information and communication technology (ICT) networks. It summarizes the research in three primary areas: attack kinds, technologies, and datasets. NIDS models have been trained and tested on a variety of datasets, including the KDD dataset, with the goal of improving classification rates and computational effectiveness. The survey describes the various capabilities and uses of a variety of NIDS technologies, such as ABTrap, RNN, CNN, Naive Bayes, Random Forest, and Decision Trees. Furthermore, the abstract discusses the frequency of Denial of Service (DoS) and Distributed Denial of Service (DDoS) assaults, emphasizing the necessity of strong defence mechanisms in Network Intrusion Detection Systems (NIDS) to guarantee network availability and security against constantly changing cyberthreats.
Keywords	IDS, NIDS, Dos, DDoS, KDD-Cup99, AB-Trap, RNN, CNN, Naive Bayes, Random Forest, Decision Tree, NSL-KDD, LSTM-AE
Field	Engineering
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-06-02
Cite This	A Study on Network Intrusion Detection System - Mohammed Kaif, Prajwal P, Laxmi V - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.20214
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.20214
Short DOI	https://doi.org/gtxrsm

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