A Study on Network Intrusion Detection System
Mohammed Kaif -, P - Prajwal, Vijay Laxmi · International Journal For Multidisciplinary Research · 2024
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.