[HTML][HTML] A systematic literature review of methods and datasets for anomaly-based network intrusion detection
As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …
threatening. Network intrusion detection has been widely accepted as an effective method to …
A comprehensive survey on feature selection in the various fields of machine learning
Abstract In Machine Learning (ML), Feature Selection (FS) plays a crucial part in reducing
data's dimensionality and enhancing any proposed framework's performance. However, in …
data's dimensionality and enhancing any proposed framework's performance. However, in …
Fusion of statistical importance for feature selection in Deep Neural Network-based Intrusion Detection System
Abstract Intrusion Detection System (IDS) is an essential part of network as it contributes
towards securing the network against various vulnerabilities and threats. Over the past …
towards securing the network against various vulnerabilities and threats. Over the past …
Performance analysis of intrusion detection systems using a feature selection method on the UNSW-NB15 dataset
SM Kasongo, Y Sun - Journal of Big Data, 2020 - Springer
Computer networks intrusion detection systems (IDSs) and intrusion prevention systems
(IPSs) are critical aspects that contribute to the success of an organization. Over the past …
(IPSs) are critical aspects that contribute to the success of an organization. Over the past …
Machine learning methods for cyber security intrusion detection: Datasets and comparative study
The increase in internet usage brings security problems with it. Malicious software can affect
the operation of the systems and disrupt data confidentiality due to the security gaps in the …
the operation of the systems and disrupt data confidentiality due to the security gaps in the …
[HTML][HTML] A deep learning technique for intrusion detection system using a Recurrent Neural Networks based framework
SM Kasongo - Computer Communications, 2023 - Elsevier
In recent years, the spike in the amount of information transmitted through communication
infrastructures has increased due to the advances in technologies such as cloud computing …
infrastructures has increased due to the advances in technologies such as cloud computing …
Benchmarking of machine learning for anomaly based intrusion detection systems in the CICIDS2017 dataset
An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions
With the increase in the usage of the Internet, a large amount of information is exchanged
between different communicating devices. The data should be communicated securely …
between different communicating devices. The data should be communicated securely …
Building an efficient intrusion detection system based on feature selection and ensemble classifier
Y Zhou, G Cheng, S Jiang, M Dai - Computer networks, 2020 - Elsevier
Intrusion detection system (IDS) is one of extensively used techniques in a network topology
to safeguard the integrity and availability of sensitive assets in the protected systems …
to safeguard the integrity and availability of sensitive assets in the protected systems …
A review of feature selection and its methods
B Venkatesh, J Anuradha - Cybernetics and information technologies, 2019 - sciendo.com
Nowadays, being in digital era the data generated by various applications are increasing
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …